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Background Hepatocellular carcinoma (HCC) is a highly malignant type of tumor that is insensitive to cytotoxic chemotherapy and often develops drug resistance. Nevadensin, a bioflavonoid, exhibits anti-cancer properties in some cancers. However, the precise underlying mechanism of nevadensin against liver cancer are poorly understood. We aim to evaluate the efficacy as well as the molecular mechanism of nevadensin in the treatment of liver cancer. Methods Effects of nevadensin on HCC cell proliferation and apoptosis were detected using EdU labeling and flow cytometry assays. The molecular mechanism of nevadensin on HCC was determined using RNAseq. The effects of nevadensin on hippo-Yap signaling were verified using western blot and RT-PCR. Results In this study, we show that nevadensin significantly inhibits growth of HCC cells via inducing cell cycle arrest and apoptosis. RNAseq analysis showed that nevadensin regulates multiple functional signaling pathways associated with cancer including Hippo signaling. Western Blot analysis revealed that nevadensin notably induces activation of the MST1/2- LATS1/2 kinase in HCC cells, further resulting in the primary effector molecule YAP phosphorylation and subsequent degradation. These results indicated that nevadensin might exert its anti-HCC activity through the Hippo-ON mechanism. Moreover, nevadensin could increase the sensitivity of HCC cells to sorafenib by down-regulating YAP and its downstream targets. Conclusions The present study indicates that nevadensin could be a potential effective approach to treating HCC, and overcoming sorafeni resistance via inducing activation of Hippo signaling.

As a globally important staple crop, wheat seeds provide us with nutrients and proteins. The trend of healthy dietary has become popular recently, emphasizing the consumption of whole-grain wheat products and the dietary benefits. However, the dynamic changes in nutritional profiles of different wheat seed regions (i.e., the embryo, endosperm and outer layers) during developmental stages and the molecular regulation have not been well studied. Here, we provide this multi-omic resource of wheat seeds and describe the generation, technical assessment and preliminary analyses. This resource includes a time-series RNA-seq dataset of the embryo, endosperm and outer layers of wheat seeds and their corresponding metabolomic dataset, covering the middle and late stages of seed development. Our RNA-seq experiments profile the expression of 63,708 genes, while the metabolomic data includes the abundance of 984 metabolites. We believe that this was the first reported transcriptome and metabolome dataset of wheat seeds that helps understand the molecular regulation of the deposition of beneficial nutrients and hence improvements for nutritional and processing quality traits.

Central carbon metabolism (CCM), including glycolysis, tricarboxylic acid cycle and the pentose phosphate pathway, is the most fundamental metabolic process in the activities of living organisms that maintains normal cellular growth. CCM has been widely used in microbial metabolic engineering in recent years due to its unique regulatory role in cellular metabolism. Using yeast and Escherichia coli as the representative organisms, we summarized the metabolic engineering strategies on the optimization of CCM in eukaryotic and prokaryotic microbial chassis, such as the introduction of heterologous CCM metabolic pathways and the optimization of key enzymes or regulatory factors, to lay the groundwork for the future use of CCM optimization in metabolic engineering. Furthermore, the bottlenecks in the application of CCM optimization in metabolic engineering and future application prospects are summarized.

Background We aimed to analyze the genotype-phenotype correlations of STXBP1 pathogenic variants, prognostic factors and the treatment choices in a case-series of STXBP1-related disorders from China. Methods The clinical data and genetic results of the children diagnosed with STXBP1-related disorders at Xiangya hospital from 2011 to 2019 were collected retrospectively, and analyzed. We divided our patients into groups for comparison purposes: patients with missense variants and nonsense variants, patients who are seizure-free and not seizure-free, patients with mild to moderate intellectual disability (ID) and severe to profound global developmental delay (GDD). Results Nineteen patients were enrolled: 17 (89.5%) unrelated and 2 (10.5%) familial. Twelve (63.2%) were females. Developmental epileptic encephalopathy (DEE) was observed in 18 (94.7%) patients and ID alone in 1 (5.3%) individual. Thirteen patients (68.4%) had profound ID/GDD, 4 (23.53%) severe, 1 (5.9%) moderate and 1 (5.9%) mild. Three patients (15.8%) with profound ID died. A total of 19 variants were detected: pathogenic (n = 15) and likely pathogenic (n = 4). Seven were novel variants: c.664-1G>-, M486R, H245N, H498Pfs*44, L41R, L410del, and D90H. Of the 8 previous reported variants, 2 were recurrent: R406C and R292C. Anti-seizure medications were used in combinations, and 7 patients became seizure-free, and most of them achieved seizure freedom within the first 2 years of life irrespective of the type of the mutation. Effective medications for the seizure-free individuals included adrenocorticotropic (ACTH) and/or levetiracetam and/or phenobarbital and/or sodium valproate and/or topiramate and/or vigabatrin and/or nitrazepam. There was no correlation between the types of pathogenic variants and the phenotypes. Conclusion Our case-series showed that there is no genotype-phenotype correlation in patients with STXBP1-related disorders. This study adds 7 novel variants which expand the spectrum of STXBP1-related disorders. Combinations of levetiracetam and/or sodium valproate and/or ACTH and/or phenobarbital and/or vigabatrin and/or topiramate and/or nitrazepam were more often associated with seizure freedom in our cohort within 2 years of life.

The monitoring of wooden pagodas is a very important task in the restoration of wooden pagodas. Traditionally, this labor has always been carried out by surveying personnel, who manually check all parts of the pagoda, which not only consumes huge manpower, but also suffers from low efficiency and measurement errors. This article evaluates the feasibility of combining portable 3D light detection and ranging (LiDAR) scanning and unmanned aerial vehicle (UAV) photogrammetry to perform these inspection tasks easily and accurately. The wooden pagoda's exterior picture and inside point cloud are acquired using a UAV and a LiDAR scanner, respectively. We propose a feature−based global alignment method to register the site point cloud. The error equation of the column of observed values is utilized as the beginning value of the feature constraint for global leveling. The beam method leveling model solves the spatial transformation parameters and the unknown point leveling values. Then, the Structure from Motion (SfM) algorithm of computer vision is used to realize the fusion of the dense point cloud of the exterior of the wooden pagoda generated from multiple non−measured images by global optimization and the LiDAR point cloud of the interior of the wooden pagoda to obtain the complete point cloud of the wooden pagoda, which makes the deformation monitoring of the pagoda more detailed and comprehensive. After experimental verification, the overall registration accuracy of the Yingxian wooden pagoda reaches 0.006 m. Compared with the scanning point cloud data in 2018, the model is more accurate and complete. By analyzing and comparing the data of the second floor of the wooden pagoda, we knew that the inclination of a second bright layer and a second dark layer is still developing steadily. Overall, the western outer trough inclines thoughtfully, and the column frame slopes from southwest to northeast. Some internal columns showed a negative offset in 2020, and the deformation analysis of a single column was realized by comparing it with the standard column model. The main contribution of this method lies in the effective integration of UAV images and point cloud data to provide accurate data sources for good modeling. This research will provide theoretical and methodological support for the digital protection of architectural heritage and GIS data modeling. The analysis results can provide a scientific basis for the restoration scheme design.

Cooperation between upstream suppliers and downstream manufacturers in technology investment is a popular way to improve production technology for reducing suppliers' production costs of key components. Technology investments undertaken by manufacturers and wholesale price discount contract provided by suppliers have an important impact on their cooperation. This paper explores whether a supplier should cooperate with two downstream competing manufacturers to accept their technology investments to reduce the supplier's production cost of a key component. Specifically, we consider the following three cooperation strategies: the supplier does not accept manufacturers' technology investments, only accepts one manufacturer's technology investment and accepts both manufacturers' technology investments. Our results demonstrate that the wholesale price discount contract and the technology investment can enhance the profits of the supplier and two manufacturers when the discount degree is low. Further, we conclude that when the discount degree is relatively low or when the discount degree and the technology investment efficiency are relatively high, the supplier's optimal cooperation strategy with two manufacturers is to accept both manufacturers' technology investments for reducing the supplier's production cost of the key component and both manufacturers are also willing to invest simultaneously. At last, we extend the model to the asymmetric potential market size and show that our theoretical results are robust.

Background Occupational exposure may be associated with an increased risk of developing hyperuricemia. This study sheds lights on the association between occupational exposure and hyperuricemia in steelworkers. Method A nested case–control study was conducted within a cohort of workers in steel companies to explore the association between occupational exposure and hyperuricemia. The case group consisted of a total of 641 cases of hyperuricemia identified during the study period, while 641 non-hyperuricemia subjects with the same age and gender distribution were randomly selected from the cohort as the control group. Results The incidence rate of hyperuricemia among workers in the steel company was 17.30%, with an incidence density of 81.32/1,000 person-years. In comparison to the reference group, the risks of developing hyperuricemia for steelworkers undergoing ever shifts, current shifts, heat exposure, and dust exposure were 2.18 times, 1.81 times, 1.58 times and 1.34 times higher respectively. The odds ratios (ORs) and 95% confidence intervals (CIs) were 1.87(1.12–3.13) and 2.02(1.21–3.37) for the cumulative number of days of night work at 0–1,972.80 and ≥ 1,972.80 (days), respectively. Compared to the group with the cumulative heat exposure of 0 (°C/year), the ORs (95% CI) for the risk of developing hyperuricemia in the groups with the cumulative heat exposure of 0–567.83 and ≥ 567.83 (°C/year) were 1.50(1.02–2.22) and 1.64(1.11–2.43), respectively. The OR (95% CI) for the risk of developing hyperuricemia was 1.56(1.05–2.32) at the cumulative dust exposure of ≥ 30.02 (mg/m3/year) compared to that at the cumulative dust exposure of 0 (mg/m3/year). Furthermore, there was a multiplicative interaction between heat exposure and dust exposure in the development of hyperuricemia. Conclusion Shift work, heat, and dust are independent risk factors for the development of hyperuricemia in steelworkers. Additionally, there is a multiplicative interaction between heat exposure and dust exposure in the development of hyperuricemia. Interventions for shift work, heat and dust may help to reduce the incidence rate of hyperuricemia and improve the health of steelworkers.

With the change in environment and lifestyle, the number of diabetic patients is increasing rapidly. Diabetes has become one of the most important chronic diseases affecting the health of the Chinese people, and complications, disability, death and treatment costs caused by diabetes have placed a heavy burden on families and society. If the high-risk population of diabetes can be identified and the adverse lifestyle can be changed as soon as possible, the incidence of diabetes can be reduced or the onset of diabetes can be slowed down. Risk prediction model can accurately predict the risk of disease and has been widely used in the field of health management and medical care. This study was based on the special occupational group of steel workers, the risk prediction model of type 2 diabetes was established by using convolutional neural network, and the feasibility of the model was discussed. The results showed that the prediction accuracy of the established model in the training set, verification set, and test set is relatively high, which is 94.5%, 91.0%, and 89.0%, respectively. The area under the ROC curve was 0.950 (95 CI 0.938–0.962), 0.916 (95 CI 0.888–0.945), and 0.899 (95 CI 0.899–0.939), respectively, indicating that the model can accurately predict the risk of type 2 diabetes among steel workers, provide a basis for self-health management of steel workers, facilitate the rational allocation of medical and health resources and the development of health services, and provide a basis for government departments to make decisions.

Optimal contract regulates the expected activities of both principals and agents, and influences how the gains from the cooperation are shared between the two participators. Thus, it is necessary and wise for principals to seek for the optimal contracts during the period of negotiations. To determine the optimal contracts, there are several kinds of agency models based on different measures, such as probability measure, capacity measure, credibility measure and uncertainty measure. This paper primarily presents a comparative review of random agency model, fuzzy agency model and uncertain agency model. This comparative review is aimed at not only summarizing the structure and feature of each agency model but also guiding on how to identify the most suitable agency model for each specific principal agent problem. Motivated by this idea, these three classes of agency models are respectively investigated about their structure, feature and application, and then an empirical comparison among these models is basically carried out from several aspects, such as information diversity, decision rule and calculation. As a significant contribution, the comparative result in this paper provides the guidance for the principals on how to identify the most suitable agency model for each special principal agent problem in a certain setting.

Nowadays, along with increased public demands on the high-quality green fresh product, the downstream retailer has to spend in the packaging and cold chain transportation and the upstream farmer needs to invest more in green fresh products producing. In this paper, we investigate a green fresh product supply chain problem, in which the retailer transports and sells green fresh products to the ultimate consumer while the farmer produces green fresh product through spending a greenness improvement investment and sells green fresh products to the retailer. Since the fresh product is perishable, the retailer needs to make a costly freshness-keeping effort. Obviously, the freshness-keeping effort, the price, and the greenness improvement level will affect the demand. Thus, to demonstrate the game structure between the retailer and the farmer, a decentralized model without cost sharing, a decentralized Stackelberg cost sharing model, and a Nash bargaining model with cost sharing are formulated. Results show that: (1) The equilibrium decisions under Stackelberg model with cost sharing are larger than that of the Nash bargaining model with cost sharing, while equilibrium decisions in the decentralized model without cost sharing are the least. (2) Both greenness improvement levels in Stackelberg cost sharing contract and Nash bargaining are greater than that in decentralized model without cost sharing. (3) The retailer’s profits in Stackelberg cost sharing contract and Nash bargaining are larger than that in decentralized case without cost sharing, while the farmer’s profits in Stackelberg cost sharing contract and Nash bargaining are larger than in decentralized model without cost sharing in certain conditions. Meanwhile, a numerical example is given to illustrate the results we obtained in the theoretical analysis process.

Along with the significant improvement of environmental consciousness, consumers not only consider the price and quality level of products, but also pay more attention to their green level. In order to strengthen the competitive advantage, the manufacturers should consider the green level of products in addition to their price and the quality level. In this paper, we investigate the green investment of two competing manufacturers in a supply chain based on price and quality competition and analyze the effect of green investment on the quality level of the product. The research shows that the manufacturer is willing to make a green investment with a relatively low value of green sensitivity regardless of whether the manufacturer’s rival makes a green investment. Further, we find that the profit of the manufacturer who makes a green investment is greater than the profit of the manufacturer who does not invest regardless of the market size. When both competing manufacturers make green investments, the profit of the manufacturer who is in a large potential market is higher than that of the manufacturer who is in a small potential market. While in a same potential market, the profits of the two competing manufacturers are the same. Finally, we conclude that the green investment counterintuitively will not always improve the quality level of the products.

Background The prevalence of metabolic syndrome continues to rise sharply worldwide, seriously threatening people’s health. The optimal model can be used to identify people at high risk of metabolic syndrome as early as possible, to predict their risk, and to persuade them to change their adverse lifestyle so as to slow down and reduce the incidence of metabolic syndrome. Methods Design existing circumstances research. A total of 1468 workers from an oil company who participated in occupational health physical examination from April 2017 to October 2018 were included in this study. We established the Logistic regression model, the random forest model and the convolutional neural network model, and compared the prediction performance of the models according to the F1 score, sensitivity, accuracy and other indicators of the three models. Results The results showed that the accuracy of the three models was 82.49,95.98 and 92.03%, the sensitivity was 87.94,95.52 and 90.59%, the specificity was 74.54, 96.65 and 94.14%, the F1 score was 0.86,0.97 and 0.93, and the area under ROC curve was 0.88,0.96 and 0.92, respectively. The Brier score of the three models was 0.15, 0.08 and 0.12, Observed-expected ratio was 0.83, 0.97 and 1.13, and the Integrated Calibration Index was 0.075,0.073 and 0.074, respectively, and explained how the random forest model was used for individual disease risk score. Conclusions The study showed that the prediction performance of random forest model is better than other models, and the model has higher application value, which can better predict the risk of metabolic syndrome in oil workers, and provide corresponding theoretical basis for the health management of oil workers.

This paper investigates an option contract for emergency material reserve because of quality catastrophic change. The quality catastrophic change happens randomly and the realized number can not be observed until it happened. Thus, it is necessary to reserve some emergency material beforehand. However, the demander is not qualified to make the storage. Meanwhile, the supplier has no motivation to make storage for the demander. Thus, an option contract is proposed to encourage the supplier to make backup for the demander and share the shortage cost if the backup less than the realized option order quantity. Three models are discussed: the centralized model without option, the decentralized model without option, and the decentralized model with option. The results demonstrate that the order quantity for the first time under the centralized scenario is greater than that under the decentralized model without option. And, the order of the purchase quantity for the first time under the three scenarios depend on the parameters decided by the both players. Meanwhile, through analysing, the effective range of option fee is proved to be limited to an interval.

Differential scanning calorimetry (DSC) and polarized optical microscopy were used to comparatively investigate the multiple melting behavior and isothermal crystallization kinetic of pure PET and PET/Na+-MMT nanocomposites prepared through solid-state mechanochemical method and conventional method. The results showed that both pure PET and Na+-MMT-filled PET system isothermally treated at different crystallization temperature exhibited three melting endotherms, including peak I, II and III in the DSC heating process. The increases in both crystallization temperature and Na+-MMT loading and the mechanochemical pan-milling prove to be beneficial to the formation of crystals related to endotherm II in the primary crystallization process. The mechanochemical pan-milling effect and the increase in the Na+-MMT loading also decrease the size of the formed spherulite. The investigation of isothermal crystallization kinetics indicated that the calculated Avrami exponent n of the milled sample (PETSNx) shows the higher value than that of both pure PET and the conventional unmilled sample (PETCNx) and also increases with increasing the Na+-MMT content. In addition, the calculated crystallization activation energy of PETSNx is found to be lower than that of pure PET as well as PETCNx.

The high-energy above-threshold ionization of a model-H atom (with 1s state and the same binding energy as H atom) in a few-cycle laser pulse is investigated by using the improved strong-field approximation (ISFA), where the spherical shell potential is used as the rescattering potential. The results obtained from numerically solving time-dependent Schrodinger equation(TDSE) are regarded as the benchmark results. Our results show that the energy distributions in high-energy region obtained from ISFA calculations using the spherical shell potential may either match or be better than those from ISFA using Yukawa potential and zero-range potential in the laser with wavelengths of 800 and 1200 nm. In addition, the influence of the rescattering potential on the density of probability at different ejection angles is also discussed in this paper.

Background Geosocial networking smartphone applications (apps) are popular tools for seeking sexual partners among men who have sex with men (MSM). We evaluated app use and risk of sexually transmitted infections (STIs) in app-using MSM (app-users) by a systematic review and meta-analysis. Methods A literature search for relevant studies was performed. We extracted date of STIs (ever being diagnosed with human immunodeficiency virus [HIV], syphilis, gonorrhea and chlamydia) and sexual behavior (e.g., number of app-met partners, unprotected anal/oral sex, HIV testing) from the eligible studies. Pooled proportions and odds ratios (ORs) with 95% confidence intervals (95% CIs) were estimated. Results Twenty-five studies were included. The self-reported prevalence of prior diagnosis of HIV among app-users ranged from 2.2 to 37.7%, and the pooled prevalence of HIV infection was 6% (95% CI, 4–11%). Compared with non-users, app-users were more likely to have gonorrhea (OR = 2.36; 95% CI, 2.07–2.70) and chlamydia (OR = 2.22; 95% CI, 1.92–2.56). The two groups were similar in terms of diagnoses of HIV (OR = 0.89, 95% CI, 0.68–1.16) and syphilis (OR = 1.92; 95% CI, 0.91–4.03). However, when one study that caused substantial heterogeneity was omitted, the pooled OR for app-users to contract syphilis became 3.00 (95% CI, 1.84–4.91) . Conclusions MSM who seek sexual partners using apps may be more likely to have STIs as than are non-users. Electronic supplementary material The online version of this article (10.1186/s12889-018-6092-3) contains supplementary material, which is available to authorized users.

In the version of this article originally published, some cases that were presented in Fig. 3 should have been underlined but were not. The appropriate cases have now been underlined. The error has been corrected in the print, PDF and HTML versions of the article.

This paper investigates a novel job search problem in a hybrid uncertain environment. Hybrid uncertainty consists of the randomness in search process and the fuzziness of offered wage. The expected value criterion and the risk tolerance criterion are designed for the job searcher to accept or reject the job offer. Under these two criteria, computing formulas to calculate the expected return of the job searcher are presented. Simultaneously, the average search times and the average chances that search returns exceed reservation wages are provided. Finally, a numerical example is given to illustrate the relationships between the expected returns of the job searcher under two criteria, and the relationships between two average chances as well.

This paper studies the optimal placement of pyroelectric infrared (PIR) sensors in developing the infrared motion sensing system for human motion localization. In particular, we explore the use of genetic algorithm (GA) in optimizing both the deployment and the modulated field of view (FOV) of the PIR sensors for improving the localization performance. Two criteria, the average and maximum localization errors, are used to evaluate the localization performance. In addition, the numerical analysis is presented to offer a guidance on the searching spaces of the design parameters in implementing GA optimization. The proposed GA-based design approach is validated by means of both simulation and experimental studies in the context of human-following mobile robots.

Background Danqi pill (DQP) is one of the most widely prescribed formulas and has been shown to have remarkable protective effect on coronary heart disease (CHD). However, its regulatory effects on lipid metabolism disorders haven’t been comprehensively studied so far. We aimed to explore the effects of DQP on Peroxisome Proliferator activated receptors α (PPARα), lipid uptake-transportation-metabolism pathway and arachidonic acid (AA)-mediated inflammation pathway in rats with CHD. Methods 80 Sprague-Dawley (SD) Rats were randomly divided into sham group, model group, positive control group and DQP group. Rat model of CHD was induced by ligation of left ventricle anterior descending artery and fed with high fat diet in all but the sham group. Rats in sham group only underwent thoracotomy. After surgery, rats in the positive control and DQP group received daily treatments of pravastatin and DQP respectively. At 28 days after surgery, rats were sacrificed and plasma lipids were evaluated by plasma biochemical detection. Western blot and PCR were applied to evaluate the expressions of PPARα, proteins involved in lipid metabolism and AA pathways. Results Twenty eight days after surgery, dyslipidemia developed in CHD model rats, as illustrated by elevated plasma lipid levels. Expressions of apolipoprotein A-I (ApoA-I), cluster of differentiation 36 (CD36) and fatty acid binding protein (FABP) in the heart tissues of model group were down-regulated compared with those in sham group. Expressions of carnitine palmitoyl transferase I (CPT-1A) and lipoproteinlipase (LPL) were also reduced significantly. In addition, levels of phospholipase A2 (PLA2) and cyclooxygenase 2 (COX-2) were up-regulated. Expressions of Nuclear factor-κB (NF- κB) and signal transducer and activator of transcription 3 (STAT3) also increased. Furthermore, Expression of PPARα decreased in the model group. DQP significantly up-regulated expressions of ApoA-I and FABP, as well as the expressions of CPT-1A and CD36. In addition, DQP down-regulated expressions of PLA2, COX-2 and NF-κB in inflammation pathway. Levels of STAT3 and LPL were not affected by DQP treatment. In particular, DQP up-regulated PPARα level significantly. Conclusions DQP could effectively regulate lipid uptake-transportation-metabolism process in CHD model rats, and the effect is achieved mainly by activating ApoA-I-CD36-CPT-1A molecules. Interestingly, DQP can up-regulate expression of PPARα significantly. The anti-inflammatory effect of DQP is partly exerted by inhibiting expressions of PLA2-COX2 -NF-κB pathway.

The role of frequency in the range 20 through 300 Hz on the breakdown voltage and the breakdown path is studied in cross-linked polyethylene (XLPE) cable insulation using embedded needle. A maximum breakdown voltage of 25 kV is found at 240 Hz, and side channels are observed on the flank of the main channel of the electrical breakdown path. Fractal analysis of the side channel is carried out and it is induced that the frequency dependence of the fractal dimension D of the side channel are similar to that of the electrical trees before breakdown. It is suggested that the space charge can be injected from the needle tip. This leads to partial discharge causing progress of the electrical tree and the breakdown path. Space charge will also result in field-moderating cloud around the needle tip and turn to sidewall charges in the side channels. The frequency dependence of the breakdown voltage of the XLPE with the embedded needle can be clarified based on the fractal analysis of the side channel and the electrical tree of the XLPE insulation.

This paper investigates an uncertain price discrimination problem in labor market, in which the employee's capability is his/her private information and characterized as an uncertain variable. To maximize the employer's welfare, an uncertain price discrimination model in labor market is established. Moreover, a crisp equivalent form of the model is given, and the analytic solution is therefore obtained by employing variational method. This optimal solution shows that both the productivity and the wage are increasing with respect to the employee's capability.

Integrated management that combines different methods is being actively pursued in the control of postharvest disease. In this study, the biocontrol yeast Cryptococcus laurentii and ultraviolet-C (UV-C) treatment were evaluated for controlling infection following artificial inoculation with Botrytis cinerea or Alternaria alternata, and natural infection in tomato fruit. Applied separately, C. laurentii and UV-C (4 kJ m−2) effectively inhibited decay caused by B. cinerea or A. alternata, and natural infection. The combination of C. laurentii and UV-C showed better control efficiency. UV-C treatment did not affect yeast growth in fruit wounds, while the treatment induced the transcript expression of β-1,3-glucanase, phenylalanine ammonia-lyase, peroxidase and superoxide dismutase based on real-time PCR analysis, as well as increased the activity of these enzymes in tomato fruit. Results indicate that the mechanism by which UV-C enhanced the biocontrol efficacy of C. laurentii may be associated with the elicitation of defense response in tomato fruit.

This paper presents a new distributed direction-sensitive infrared sensing approach for fall detection in elderly healthcare applications. Pyroelectric infrared (PIR) sensors are employed in sensing human activities. For capturing the characteristics of human normal and abnormal activities, three modules of a direction-sensitive PIR sensor are organized using a distributed sensing structure. The advantage of using the distributed sensing paradigm is that the synergistic motion patterns of head, upper-limb and lower-limb can be efficiently encoded and thus the more discriminative features can be captured. This is the new consideration of using PIR sensors in building a full detection system. In addition, a two-layer hidden Markov model is developed for recognizing a fall event based on the multidimensional signals of the distributed infrared sensing system. Experimental studies are conducted to validate the proposed method.

Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively increased by using flood forecast information and flood control forecast operation mode. In this paper, Dahuofang Reservoir is selected as a case study. At first, the distribution pattern and the bound of forecast error which is a key source of risk are analyzed. Then, based on the definition of flood risk, the risk of dynamic control of reservoir flood limited water level within different flood forecast error bounds is studied. The results show that, the dynamic control of reservoir flood limited water level with flood forecast information can increase the floodwater utilization rate without increasing flood control risk effectively and it is feasible in practice.

Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was established according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respectively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combination weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the assessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.

The objective of the study was to explore the pathogenesis of mesial temporal lobe epilepsy (MTLE) and the mechanism of valproate administration in the early stage of MTLE development. We performed a global comparative analysis and function classification of differentially expressed proteins using proteomics. MTLE models of developmental rats were induced by lithium-pilocarpine. Proteins in the hippocampus were separated by 2-DE technology. PDQuest software was used to analyze 2-DE images, and MALDI-TOF-MS was used to identify the differentially expressed proteins. Western blot was used to determine the differential expression levels of synapse-related proteins synapsin-1, dynamin-1 and neurogranin in both MTLE rat and human hippocampus. A total of 48 differentially expressed proteins were identified between spontaneous and non-spontaneous MTLE rats, while 41 proteins between MTLE rats and post valproate-treatment rats were identified. All of the proteins can be categorized into several groups by biological functions: synaptic and neurotransmitter release, cytoskeletal structure and dynamics, cell junctions, energy metabolism and mitochondrial function, molecular chaperones, signal regulation and others. Western blot results were similar to the changes noted in 2-DE. The differentially expressed proteins, especially the proteins related to synaptic and neurotransmitter release function, such as synapsin-1, dynamin-1 and neurogranin, are probably involved in the mechanism of MTLE and the pharmacological effect of valproate. These findings may provide important clues to elucidate the mechanism of chronic MTLE and to identify an optimum medication intervention time and new biomarkers for the development of pharmacological therapies targeted at epilepsy.

The ill-conditioned stable inversion is studied for slightly nonminimum phase systems whose zero dynamics is singularly perturbed, that is, the relative degree is ill-defined. For these systems, we show that there exists an inherent limitation in the bandwidth of a reference trajectory to be tracked when a well-conditioned feedforward input via stable inversion is sought. We assert that, when the violation of this limitation occurs, the so-called reference trajectory redesign is called for. Our analysis results can provide an explicit assessment as well as useful guidance for the reference trajectory redesign if needed.

The delay-dependent robust stability of uncertain linear neutral systems with delays is investigated. Both discrete-delay-dependent/neutral-delay-independent and neutral-/discrete-delay-dependent stability criteria will be developed. The proposed stability criteria are formulated in the form of linear matrix inequalities and it is easy to check the robust stability of the considered systems. By introducing certain Lyapunov-Krasovskii functional the mathematical development of our result avoids model transformation and bounding for cross terms, which lead to conservatism. Finally, numerical example is given to indicate the improvement over some existing results.

The blood–testis barrier (BTB) constituted by coexisting junction apparatus between Sertoli cells (SCs) plays an important role in spermatogenesis, which is a known target of various environmental toxicants. The commercial polychlorinated biphenyls mixture, Aroclor1254, has been shown to impair male reproduction by decreasing sperm count and affecting SC metabolism. This study was designed to investigate the effects of Aroclor1254 on the BTB integrity and elucidate the underlying mechanisms. We found that Aroclor1254 treatment in rats (1 or 3 mg/kg per day for 21 consecutive days) and in primary cultured SCs (5 or 10 μg/ml for 48 h) could induce BTB disruption via p38 MAPK pathway, concurrently with increments in junction proteins (JAM-A, N-cadherin, and β-catenin) endocytosis, and occludin ubiquitination. Either inhibition of caveolin-dependent membrane protein internalization by cholesterol oxidase or silencing E3 ubiquitine ligase Itch by small interfering RNA could partially counteract the effects of Aroclor1254 on the barrier function of cultured SCs. These results demonstrate that Aroclor1254 disrupts the BTB function by promoting the caveolin-dependent endocytosis and ubiquitine–proteasome degradation of junction proteins through the p38 MAPK pathway, which might be the potential reasons for its negative effects on spermatogenesis and male reproduction.

High harmonics extending to X-rays have been generated from gases by intense lasers. To establish these coherent broadband radiations as an all-purpose tabletop light source for general applications in science and technology, new methods are needed to overcome the present low conversion efficiencies. Here we show that the conversion efficiency may be drastically increased with an optimized two-color pulse. By employing an optimally synthesized 2-µm mid-infrared laser and a small amount of its third harmonic, we show that harmonic yields from sub- to few-keV energy can be increased typically by ten-fold over the optimized single-color one. By combining with favorable phase-matching and together with the emerging high-repetition MHz mid-infrared lasers, we anticipate efficiency of harmonic yields can be increased by four to five orders in the near future, thus paving the way for employing high harmonics as useful broadband tabletop light sources from the extreme ultraviolet to the X-rays, as well as providing new tools for interrogating ultrafast dynamics of matter at attosecond timescales.

High-order harmonics extending to the X-ray region generated in a gas medium by intense lasers offer the potential for providing tabletop broadband light sources but so far are limited by their low conversion efficiency. Here we show that harmonics can be enhanced by one to two orders of magnitude without an increase in the total laser power if the laser's waveform is optimized by synthesizing two- or three-colour fields. The harmonics thus generated are also favourably phase-matched so that radiation is efficiently built up in the gas medium. Our results, combined with the emerging intense high-repetition MHz lasers, promise to increase harmonic yields by several orders to make harmonics feasible in the near future as general bright tabletop light sources, including intense attosecond pulses.

The rational fraction model for the regularized inverse dynamics of a flexible manipulator is presented, the effect of this model on alleviating the ill-posed behavior of the calculated torque is demonstrated, and the implication of the regularization parameter selection on the trade-off between the tracking accuracy and the frequency bandwidth of the calculated torque is addressed as well. The validity of the proposed method is illustrated by means of a computer numeric simulation.

Pervasive healthcare is one of the most important applications of the Internet of Things (IoT). As part of the IoT, the wireless sensor networks (WSNs) are responsible for sensing the abnormal behavior of the elderly or patients. In this article, we design and implement a fall detection system called SensFall. With the resource restricted sensor nodes, it is vital to find an efficient feature to describe the scene. Based on the optical flow analysis, it can be observed that the thermal energy variation of each sub-region of the monitored region is a salient spatio-temporal feature that characterizes the fall. The main contribution of this study is to develop a feature-specific sensing system to capture this feature so as to detect the occurrence of a fall. In our system, the three-dimensional (3D) object space is segmented into some distinct discrete sampling cells, and pyroelectric infrared (PIR) sensors are employed to detect the variance of the thermal flux within these cells. The hierarchical classifier (two-layer HMMs) is proposed to model the time-varying PIR signal and classify different human activities. We use self-developed PIR sensor nodes mounted on the ceiling and construct a WSN based on ZigBee (802.15.4) protocol. We conduct experiments in a real office environment. The volunteers simulate several kinds of activities including falling, sitting down, standing up from a chair, walking, and jogging. Encouraging experimental results confirm the efficacy of our system.

Background Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to identify patterns that together explain the data as a linear combination of expression signatures. Microarray data generally includes individual estimates of uncertainty for each gene in each condition, however NMF does not exploit this information. Previous work has shown that such uncertainties can be extremely valuable for pattern recognition. Results We have created a new algorithm, least squares non-negative matrix factorization, LS-NMF, which integrates uncertainty measurements of gene expression data into NMF updating rules. While the LS-NMF algorithm maintains the advantages of original NMF algorithm, such as easy implementation and a guaranteed locally optimal solution, the performance in terms of linking functionally related genes has been improved. LS-NMF exceeds NMF significantly in terms of identifying functionally related genes as determined from annotations in the MIPS database. Conclusion Uncertainty measurements on gene expression data provide valuable information for data analysis, and use of this information in the LS-NMF algorithm significantly improves the power of the NMF technique.