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An optimized matter element decision method is proposed based on intuitionistic fuzzy set (IFS) and Choquet integral to solve the problems of equipment development scheme decision (e.g., the correlation of scheme attributes and the low decision reliability of evaluation results). First, the nonlinear programming problem of expert intuition fuzzy subjective and objective decision information difference is constructed using the Choquet integral method, and the measure values and related factors of decision attributes are solved using the optimization algorithm. Second, given the comprehensive contribution of attributes, the fuzzy measure Shapley value is employed to represent the attribute weight. Last, the matter element extension model is optimized using the attribute weight information and intuitionistic fuzzy score value, and a two-level evaluation strategy is formulated to determine the ranking and grade. On that basis, scientific decisions are made for several different schemes to be selected.

Sit-to-stand (STS) movement is a very common task for the elderly and the patients with lower limb dysfunction in daily life. We hope to summarize the methods of STS experiment and the factors affecting STS, and provide a reference for future STS experimental researches. We selected the relevant STS experimental studies, analyzed and compared the methods and results of these studies, and the suggestions for future research were made. In the exploration of STS movement experiment, human biomechanical data, kinematic data, kinetic data, time and subjective evaluation of subjects are all important indicators reflecting STS performance. External factors, individual factors of subjects and STS strategies also have a significant impact on the movement performance of STS. Simulation of human body can eliminate the influence of subjective factors on the movement of human body, and set anthropometry parameters more conveniently. We found that the influences of folding arms, hand support and knee support modes on STS need to be explored deeply. The appropriate weight reduce ratio for rehabilitation training system need to further study. We need to continue to explore new technologies to find the methods to create a human biomechanical model with higher simulation degree, improving the accuracy of the simulation.

Enhancements of edge zonal flows, radial electric fields, and turbulence are observed in electron cyclotron resonance heating-heated plasmas (Zhao et al 2013 Nucl. Fusion 53 083011). In this paper, the effects of sawtooth heat pulses on flows and turbulence are presented. These experiments are performed using multiple Langmuir probe arrays in the edge plasmas of the HL-2A tokamak. The edge zonal flows, radial electric fields, and turbulence are all enhanced by sawteeth. Propagation of the zonal flow and turbulence intensities is also observed. The delay time of the maximal intensity of the electric fields, zonal flows, and turbulence with respect to the sawtooth crashes is estimated as ∼1 ms and comparable to that of the sawtooth-triggered intermediate phases. Not only the zonal flows but also the radial electric fields lag behind the turbulence. Furthermore, the intensities of both the zonal flows and electric fields nearly linearly increase/decrease with the increase/decrease of the turbulence intensity. A double-source predator–prey model analysis suggests that a relatively strong turbulence source may contribute to the dominant zonal flow formation during sawtooth cycles.

Sit-to-stand is a common activity in daily life. It is difficult for the elderly and patients with lower limb disorders to complete this motion due to limb pain, muscle weakness, partial loss of motor control function, and physical defects in joints. An STS assistive device is a piece of automated medical equipment that can facilitate rehabilitation training for patients with lower limb disorders and improve their lower limb function. In this paper, we introduce a 3-DOF series type STS assistive device. First, we selected 26 healthy adults to carry out an STS transfer experiment, and we obtained the trajectory and velocity of each joint and the law of plantar pressure during STS motion. Second, based on the above kinematics and dynamics law, a 3-DOF series mechanism was designed. Through forward and inverse kinematics analysis, the relationship between the end-effector and the linear actuator was established. The trajectory planning of the end-effector was carried out according to the natural STS transfer trajectory, and the law of the linear actuator was obtained. The trajectory planning was verified by ADAMS. Finally, the Arduino controller was used to build the control system of the STS assistive device, and the prototype experiment was carried out.

Thermostable and alkaline- or acid-stable xylanases are more advantageous in agricultural and industrial fields. In this study, a rational structure-based design was conducted based on a thermostable GH11 xylanase TlXynA from Thermomyces lanuginosus to improved pH-tolerance. Four mutant enzymes (P1, P2, P3, and P4) and five variants (N1, N2, N3, N4, and N5) were constructed by substituting surface charged residue combinations using site-directed mutagenesis. Compared to the native enzyme, two mutants P1 and P2 showed higher acid tolerance, especially at pH 3.0, presented 50 and 40% of their maximum activity, respectively. In addition, four mutants N1, N2, N3 and N4 had higher tolerance than the native enzyme to alkaline environments (pH 7.0–9.0). At pH 9.0, the residual activities of N1, N2, N3, and N4 were 86, 78, 77, and 66%, respectively. In summary, an improved pH-tolerance design principle is being reported.

Actinomycetes , a group of Gram-positive bacteria with high GC contents, play important roles in hyperthermal lignocellulose degradation in terrestrial habitats. A functional genomics analysis revealed that lignocellulose-degrading actinomycetes have more cellulases than hemicellulases and pectinases. Additionally, the enzymes capable of degrading cellulose were mainly cellobiohydrolases belonging to glycoside hydrolase family 6, with a small number of cellulases belonging to glycoside hydrolase families 9 and 48. In addition to glycoside hydrolases, large numbers of polysaccharide monooxygenases from auxiliary activity family 10 were also identified. Therefore, actinomycetes can efficiently degrade crystalline cellulose by continuous hydrolysis and oxidation mechanisms. Furthermore, some of these enzymes with multiple structural domains can be secreted quickly into the extracellular environment through the twin-arginine translocation system. These lignocellulolytic enzymes have excellent properties, such as high enzyme activity and high temperature and alkali resistance. Therefore, the characteristics and advantages of these actinomycetes in lignocellulose degradation and secondary metabolite production make them well suited for industrial applications.

Background The biodegradation of chitin is an important part of the carbon and nitrogen cycles in nature. Speeding up the biotransformation of chitin substrates can not only reduce pollution, but also produce high value-added products. However, this process is strictly regulated by the catalytic efficiency of the chitinolytic machinery. Therefore, it is necessary to study the mode of action and compound mechanisms of different chitin-degrading enzymes in depth to improve the catalytic efficiency of the chitinolytic machinery. Results The thermophilic bacterium Streptomyces sp. F-3 showed comparatively high chitin degradation activities. To elucidate the mechanism underlying chitin hydrolysis, six chitin degradation-related enzymes were identified in the extracellular proteome of Streptomyces sp. F-3, including three chitinases (SsChi18A, SsChi18B, and SsChi18C) from the GH18 family, one GH19 chitinase (SsChi19A), one GH20 β-N-acetylhexosaminidase (SsGH20A), and one lytic polysaccharide monooxygenase (SsLPMO10A) from the AA10 family. All were upregulated by chitin. The heterologously expressed hydrolases could withstand temperatures up to 70 °C and were stable at pH values of 4 to 11. Biochemical analyses displayed that these chitin degradation-related enzymes had different functions and thus showed synergistic effects during chitin degradation. Furthermore, based on structural bioinformatics data, we speculated that the different action modes among the three GH18 chitinases may be caused by loop differences in their active site architectures. Among them, SsChi18A is probably processive and mainly acts on polysaccharides, while SsChi18B and SsChi18C are likely endo-non-processive and displayed higher activity on the degradation of chitin oligosaccharides. In addition, proteomic data and synergy experiments also indicated the importance of SsLPMO10A, which could promote the activities of the hydrolases and increase the monosaccharide content in the reaction system, respectively. Conclusions In this article, the chitinolytic machinery of a thermophilic Streptomyces species was studied to explore the structural basis for the synergistic actions of chitinases from different GH18 subfamilies. The elucidation of the degradation mechanisms of these thermophilic chitinases will lay a theoretical foundation for the efficient industrialized transformation of natural chitin. Electronic supplementary material The online version of this article (10.1186/s13068-019-1472-1) contains supplementary material, which is available to authorized users.

Additional file 1. Additional figures and tables.

The structure of xylan, which has a 1,4-linked β-xylose backbone with various substituents, is much more heterogeneous and complex than that of cellulose. Because of this, complete degradation of xylan needs a large number of enzymes that includes GH10, GH11, and GH3 family xylanases together with auxiliary enzymes. Fluorescence-assisted carbohydrate electrophoresis (FACE) is able to accurately differentiate unsubstituted and substituted xylooligosaccharides (XOS) in the heterogeneous products generated by different xylanases and allows changes in concentrations of specific XOS to be analyzed quantitatively. Based on a quantitative analysis of XOS profiles over time using FACE, we have demonstrated that GH10 and GH11 family xylanases immediately degrade xylan into sizeable XOS, which are converted into smaller XOS in a much lower speed. The shortest substituted XOS produced by hydrolysis of the substituted xylan backbone by GH10 and GH11 family xylanases were MeGlcA(2) Xyl3 and MeGlcA(2) Xyl4 , respectively. The unsubstituted xylan backbone was degraded into xylose, xylobiose, and xylotriose by both GH10 and GH11 family xylanases; the product profiles are not family-specific but, instead, depend on different subsite binding affinities in the active sites of individual enzymes. Synergystic action between xylanases and β-xylosidase degraded MeGlcA(2) Xyl4 into xylose and MeGlcA(2) Xyl3 but further degradation of MeGlcA(2) Xyl3 required additional enzymes. Synergy between xylanases and β-xylosidase was also found to significantly accelerate the conversion of XOS into xylose.

Strongly promoted by the development of Service-Oriented Computing and Cloud Computing technologies, a large number of functionally equivalent web services emerge on the Internet. Quality of Service (QoS) is becoming a key factor to distinguish different web services. Although many Collaborative Filtering (CF) based approaches are recently proposed to predict the QoS of web services, the prediction accuracy are not satisfactory, since they rarely take full use of the neighbor information and latent feature information contained in the historical QoS data. Especially when the realworld QoS data is highly sparse, the previous works fail to detect the actual relationships between services. In this paper, we present a novel hybrid web service QoS prediction approach that systematically combines the memory-based CF and model-based CF. Firstly a non-negative matrix factorization model for web service QoS prediction is presented. Then an Expectation-Maximization (EM) based approach is designed to learn the model for making further prediction. The service neighbor information, which integrates the direct similarity and transitive indirect similarity of services to handle the data sparsity problem, is introduced into EM based learning process to make the prediction results more accurate. Large-scale real-world experiments are conducted using the WSDREAM QoS dataset. The experimental results demonstrate that our approach can achieve better prediction accuracy than other state-of-the-art approaches.

In this study, an empirical mode decomposition (EMD) based least square support vector machine (LSSVM) ensemble adaptive learning paradigm is proposed for time series forecasting. For this purpose, the original time series are first decomposed into several intrinsic mode functions (IMFs) and one residual component. Then phase space reconstruction (PSR) is done in each component, where the samples are put into LSSVM for training. Particle swarm optimization algorithm (PSO) is used to achieve the adaptive optimization of forecasting models in different components, which makes LSSVMs better describe the signal characteristics in different scales, thus greatly improves the efficiency and accuracy of the learning and training; Finally, the forecasting values of the original series are obtained through the reconstruction of the forecasting values in each component. For illustration and verification, the spare parts cost series for a vessel is used to test the effectiveness of the proposed EMD-LSSVM-PSO ensemble adaptive learning methodology. Empirical results obtained demonstrate the attractiveness of the proposed method.

Xylan constituted with β-1,4-D-xylose linked backbone and diverse substituted side-chains is the most abundant hemicellulose component of biomass, which can be completely and rapidly degraded into fermentable sugars by Aspergillus niger. This is of great value for obtaining renewable biofuels and biochemicals. To clarify the underlying mechanisms associated with highly efficient xylan degradation, assimilation, and metabolism by A. niger, we utilized functional proteomics to analyze the secreted proteins, sugar transporters, and intracellular proteins of A. niger An76 grown on xylan-based substrates. Results demonstrated that the complete xylanolytic enzyme system required for xylan degradation and composed of diverse isozymes was secreted in a sequential order. Xylan-backbone-degrading enzymes were preferentially induced by xylose or other soluble sugars, which efficiently produced large amounts of xylooligosaccharides (XOS) and xylose; however, XOS was more efficient than xylose in triggering the expression of the key transcription activator XlnR, resulting in higher xylanase activity and shortening xylanase-production time. Moreover, the substituted XOS was responsible for improving the abundance of side-chain-degrading enzymes, specific transporters, and key reductases and dehydrogenases in the pentose catabolic pathway. Our findings indicated that industries might be able to improve the species and concentrations of xylan-degrading enzymes and shorten fermentation time by adding abundant intermediate products of natural xylan (XOS) to cultures of filamentous fungi.

In this paper, an improved inductive motor model reference adaptive system (MRAS) is proposed based on an optimized full-order adaptive observer. By using of an optimized discrete model of induction motor, the proposed method can be applied to the condition of low switching frequency. The rotor speed is calculated by an adaptive scheme and used as the feedback signal for vector control. The simulation results show that the modified version of MRAS enables accurate and stable performance of speed sensorless control.

Focused on the circumstance that the equipment using demand in the short term and the development demand in the long term should be made overall plans and took into consideration in the weapons portfolio planning and the practical problem of the fuzziness in the definition of equipment capacity demand. The expression of demand is assumed to be an interval number or a discrete number. With the analysis method of epoch-era, a long planning cycle is broke into several short planning cycles with different demand value. The multi-stage stochastic programming model is built aimed at maximize long-term planning cycle demand under the constraint of budget, equipment development time and short planning cycle demand. The scenario tree is used to discretize the interval value of the demand, and genetic algorithm is designed to solve the problem. At last, a case is studied to demonstrate the feasibility and effectiveness of the proposed mode.

According to the changes in optical density ( A 600) of E. coli population in shake flask-culture and ferment culture and by using an improved data-smoothing method and then differential derivation, the two kinetic parameters, instantaneous rate ( v inst) and instantaneous increment ( v inc), as response variable were estimated and could be used to accurately characterize the kinetics of bacterial population growth. The v inst showed exponential decay pattern, while the kinetic pattern of v inc varied and depended on the inoculums size. In either case for v inst or for v inc, the kinetic curves appear neither delay period nor stable period. In fact, the pattern of kinetic growth curve were determined by the number of cells under division status, which was the result of the interaction between endogenous growth ability (which is from the continuous cell-cyclic division) and exogenous growth inhibitory force (caused by the decreased nutrients and increased metabolites). In addition, based on the dividing pattern of bacterial cell, another response variable, doubling time (Q), was also used to express the endogenous kinetic behavior. And then a bioengineering parameter, volumetric productivity, can be calculated according to the instantaneous increment ( v inc). This research can provide an effective mathematical analysis to resolve the problems of uncertainty in using logistic and Monod equation to fit the growth curve of E. coli .

Streptomyces sp. F-3 is a kind of thermophilic Streptomyces strain that can produce cellulolytic enzymes and diverse secondary metabolites. Here, we report the complete genome of this organism, whose genome length is 5,303,958 bp, containing 6,041 protein-coding genes, 69 tRNA operons, and three rRNA operons.

The filamentous fungus Aspergillus niger has become one of the most important fungi in industrial biotechnology, and it can efficiently secrete both polysaccharide-degrading enzymes and organic acids. We report here the 6,074,961,332-bp draft sequence of A. niger strain An76, and the findings provide important information related to its lignocellulose-degrading ability.

Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics and medicinal fields. In a pioneering study, Luria and Delbrück exposed E. coli to T1 phage, to investigate whether the number of resistant colonies followed the Poisson distribution. They deduced that the development of resistant colonies is independent of phage presence. Similar results have since been obtained on solid medium containing antibacterial agents. Luria and Delbrück's conclusions were long considered a gold standard for analyzing drug resistance mutations. More recently, the concept of adaptive mutation has triggered controversy over this approach. Microbiological observation shows that, following exposure to drugs of various concentrations, drug-resistant cells emerge and multiply depending on the time course, and show a process function, inconsistent with the definition of Poisson distribution (which assumes not only that resistance is independent of drug quantity but follows no specific time course). At the same time, since cells tend to aggregate after division rather than separating, colonies growing on drug plates arise from the multiplication of resistant bacteria cells of various initial population sizes. Thus, statistical analysis based on equivalence of initial populations will yield erroneous results. In this paper, 310 data from the Luria-Delbrück fluctuation experiment were reanalyzed from this perspective. In most cases, a high-end abnormal value, resulting from the non-synchronous variation of the two above-mentioned time variables, was observed. Therefore, the mean value cannot be regarded as an unbiased expectation estimate. The ratio between mean value and variance was similarly incomparable, because two different sampling methods were used. In fact, the Luria-Delbrück data appear to follow an aggregated, rather than Poisson distribution. In summary, the statistical analysis of Luria and Delbrück is insufficient to describe rules of resistant mutant development and multiplication. Correction of this historical misunderstanding will enable new insight into bacterial resistance mechanisms.

A series of experiments were performed, in which p-nitrophenyl-β-D-cellobioside (PNPC) was hydrolyzed by 1, 4-β-D-glucan-cellobiohydrolase (CBHI: EC 3.2.1.91), and O-nitrophenyl-β-D-galactoside (ONPG) was hydrolyzed by β-galactosidase (EC 3.2.1.23) under different combinations of temperature and time period. The combined effects of temperature and time on p-nitrophenyl and O-nitrophenyl formation were characterized as the change of the instantaneous reaction velocity occurrence per temperature range termed as v(inst)· T(-1). This parameter was used as a stable index to evaluate the apparent activation energy (E(a)) based on the Arrhenius approach, instead of the reaction velocity constant, k. It was found that E(a) for PNPC hydrolysis by CBHI first decreased with temperature increase and then slightly increased at higher temperature, and its minimum value was obtained just at the maximum point of v(inst). In addition, E(a) for PNPC hydrolysis by dilute sulfuric acid was not a constant, but was continuously increased with temperature. The present studies demonstrated that E(a) obtained by Arrhenius approach for the hydrolysis reaction of β-hydrolases appears to be only an empirical kinetic parameter for the dependence of the reaction velocity on temperature and time, and has no meaning in the sense of thermodynamic energy.

The dynamic growth process of Escherichia coli CVCC249 under different concentrations of antibiotics was analyzed. The results suggested that the main reason that definitive results cannot be obtained by antibiotic susceptibility testing (AST) is that the ratio of drug concentration to the population of bacteria and the combined effect of drug concentration and action time cannot be completely determined with the methods used. Based on the analysis of the growth process with a series of concentrations of gentamicin acting for a certain time, and according to the forward difference method, a novel method for AST was proposed. The net increase in turbidity of the bacterial population was used to eliminate the existing effects of resting cells, and then the recurrent coefficient for a growing sequence was used to characterize the effect of antibiotics on bacterial division, and the contour plot was used to display and analyze the combined effect of drug concentration and action time. The inhibition rate of the antibiotics can be characterized as the dynamic change in the composite function of the antibiotic concentration and action time, which indicated that the inhibition rate was dependent on the combined effect of time and concentration of antibiotics. The effectiveness of this new method has been verified with different kinds of antibiotics, such as enrofloxacin, levofloxacin, and ceftriaxone, having different antibacterial mechanisms.

ONPG disappearance and ONP appearance were synchronously measured during ONPG hydrolysis by β-galactosidase using in situ on-line UV–vis spectroscopy. Intermediate formation was determined by the formula d[ONPG]/dt − d[ONP]/dt. The combined effects of temperature and time on νinst and νinc during the conversion of ONPG to ONP were expressed by the isogram method in which contour plots were used. Based on this approach, new insights were obtained into the irreversible-continuous conversion of ONPG to ONP during hydrolysis. The intermediate was a moving mass that flowed in three-dimensional space from the substrate to the product. The results of this study support the use of the isogram method for understanding the mechanisms of enzyme-catalyzed reactions via the dynamic resolution approach.

The dynamic changes in the composition and function of both bacterial and fungal communities over time and at various depths in the compost of a 90-m(3) industrial-scale fermentor were explored using integrated meta-omics. The microbial communities in the middle layer (1.2m) of the compost developed a stable and simple structure over time, which was mainly composed of Thermobifida, Bacillus, Thermomyces and Aspergillus. According to the metaproteomic results, the bacterial community was more focused on cellulose degradation, characterized by 44% of the cellulases that were secreted by Thermobifida, while the fungal community was more likely to degrade hemicellulose, mainly via Thermomyces and Aspergillus. The results revealed that, under artificial control of the temperature and oxygen concentration, the efficiency of organic waste degradation was greatly increased and the fermentation cycle was shortened to 11 days.

The microbial community composition and function of three self-heating maize straw composts were compared by integrated meta-omics. The results revealed that the fungal communities were primarily dominated by the phylum Ascomycota (>90%) regardless of different nitrogen sources, which were exclusively composed of the Thermomyces, a genus of hemicellulose degraders. The bacterial community composition was affected by the addition of nitrogen sources, as the abundance of the Actinobacteria increased, while the Proteobacteria and Bacteroidetes decreased. Various hemicellulases and cellulases were detected in the composts, and the major xylanase secreted by Thermomyces lanuginosus was always present, revealing that it was the dominant fungus in hemicellulose hydrolysis and that bacteria and fungi might synergistically degrade lignocellulose. Thus, microbial communities in composts may develop a simple and stable structure of a dominant fungal species and limited numbers of bacterial species under the selective pressure of high temperature and maize straw as starting materials.

Filamentous fungi such as Aspergillus spp., Trichoderma spp., and Penicillium spp. are frequently used to produce high concentrations of lignocellulosic enzymes. This study examined the discrepancies in the compositions and dynamic changes in the extracellular enzyme systems secreted by Aspergillus niger ATCC1015, Trichoderma reesei QM9414, and Penicillium oxalicum 114-2 cultured on corn stover and wheat bran. The results revealed different types and an abundance of monosaccharides and oligosaccharides were released during incubation, which induced the secretion of diverse glycoside hydrolases. Both the enzyme activities and isozyme numbers of the three fungal strains increased with time. A total of 279, 161, and 183 secretory proteins were detected in A. niger, T. reesei, and P. oxalicum secretomes, respectively. In the A. niger secretomes, more enzymes involved in the degradation of (galacto)mannan, xyloglucan, and the backbone of pectin distributed mostly in dicots were detected. In comparison, although P. oxalicum 114-2 hardly secreted any xyloglucanases, the diversities of enzymes involved in the degradation of xylan and β-(1,3;1,4)-D-glucan commonly found in monocots were higher. The cellulase system of P. oxalicum 114-2 was more balanced. The degradation preference provided a new perspective regarding the recomposition of lignocellulosic enzymes based on substrate types.

Prostate cancer is a common multiple malignant tumor occurring in males. Prostate cancer mortality is the 2nd most common of all tumor types in Western countries and the mortality of morbidity is 13% in the USA. The present study aimed to investigate the anticancer effect of docetaxel on inducing the apoptosis of prostate cancer via the cofilin‑1 and paxillin signaling pathway. Treatment with docetaxel (1‑50 nM) disposed the human LNCaP prostate cancer cells for 24 h. Cell growth and cytotoxicity were subsequently measured using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and lactate dehydrogenase assay, respectively. Docetaxel-induced cell death was analyzed using flow cytometric and caspase-3 assays. Reverse transcription‑quantitative polymerase chain reaction analysis was used to detect the gene expression of cofilin‑1 and western blots were used to determine the protein expression of paxillin. Treatment with docetaxel inhibited cell growth, promoted cytotoxicity, activated apoptosis and increased caspase‑3 activity in the LNCaP cells. Notably, administration of docetaxel reduced the gene expression of cofilin‑1 and the protein expression of paxillin in the LNCaP cells. Additionally, knockdown of cofilin‑1 advanced the anticancer effect of docetaxel against LNCaP cells through suppression of the paxillin pathway. The present findings demonstrated that the anticancer effect of docetaxel induces the apoptosis of prostate cancer via the suppression of the cofilin‑1 and paxillin signaling pathways, which will assist in setting a stage for the clinical treatment of prostate cancer.

Clostridium thermocellum ( C. thermocellum ) is the dominant microorganism that can efficiently degrade lignocellulose. Extensive studies were done for secreting the cell surface-bound protein complex known as the cellulosome. C. thermocellum is regulated by carbon sources, reflected in overall multiple cellulase production and in the cellulosomal subunit profile. To produce a cellulosomal protein complex is a dynamic assembly process. In recent years, it becomes a hotspot to study how C. thermocellum senses the insoluble substrate, regulates the secretion of relevant enzymes, and assembles the supramolecular-degradation enzyme complex. This review summarized the research advance in genomics, transcriptomics, proteomics and extracellular carbohydrate-sensing mechanism in C. thermocellum, and analyzed the mechanism and dynamic process of C. thermocellum in lignocellulose degradation.

Objectives: Docetaxel was the first drug with proven survival benefit in men with castration-resistant prostate cancer. Acquired resistance to docetaxel precedes fatality in castration-resistant prostate cancer. The aims of this study were to evaluate docetaxel-sensitive and docetaxel-resistant proteomes in PC-3 cells, and to investigate the molecular mechanism of docetaxel-resistant PC-3 cells. Methods: Docetaxel-resistant PC-3 cells were developed by docetaxel dose escalation. The global profiling of the protein expression was investigated in docetaxel-sensitive and docetaxel-resistant proteomes in PC-3 cells using 2-dimensional polyacrylamide gel electrophoresis/matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Results: Forty-nine differential proteins were found in docetaxel-resistant PC-3 cells in comparison with docetaxel-sensitive PC-3 cells. Expression in 29 proteins was upregulated, whereas expression in 20 proteins was downregulated. ATP synthase and galectin-1 were involved in the formation of tumor vessels; calreticulin, cathepsin D, and cofilin were involved in tumor metastasis, and GRP78 (78-kDa glucose-regulated protein) and microtubule-associated protein-6 were involved in drug resistance of tumor. Conclusion: It is suggested that a proteomic expression difference exists between docetaxel-sensitive and docetaxel-resistant PC-3 cells, which would be helpful for further understanding the molecular mechanisms of docetaxel resistance in PC-3 cells.

Medical image data require strict security, confidentiality and integrity when transmitted between hospitals. The involvement of wireless transmission has made the medical data vulnerable to attacks like tampering, hacking etc. To dealing the challenges we have proposed a algorithm that introducing the digital watermarking technology to increase the security of medical images when they transmitted through a wireless network. The scheme uses a part of sign sequence of DWT-DCT coefficients as the feature vector of images for enhancing the robustness against common attacks and geometric attacks. The watermarking image is scrambled by Arnold transform to enhance its privacy. The experimental results show that the scheme has benefits at visual invisibility and robustness. Moreover, it can embed much more data, less complexity and more practicability than the existing watermarking techniques, because it avoids the sophisticated process of finding the Region of Interest (ROI) of medical images.

Tourist quantity is an important factor deciding economic benefits and sustainable development of tourism. Thus tourist quantity prediction becomes the important content of tourism development planning. Based on the tourist quantity of Hainan province for more than twenty years, this paper establishes tourist quantity prediction model according to RBF neural network (1), in which the principle and algorithm of RBF neural network is used. And this paper also predicts the future tourist quantity of Hainan province. The Matlab emulation result of RBF neural network model shows based on RBF neural network tourist quantity prediction model can exactly predict the future tourist quantity of Hainan province, thus providing a new idea and mean for tourist quantity prediction.

In this paper, we propose a multiple watermarks technique for video sequences. The proposed algorithm is based on the three-dimensional discrete Fourier transform (3D DFT). The video sequences are divided into different shots and key frames are selected from those shots. The 3D DFT is performed on these key frames and the coefficients of the 3D DFT are got. The sign sequence of 3D DFT coefficients is used as feature vector. Then three binary sequences are used as the watermarks and combining the concept of third-party, we describe how to embed and extract the watermarks. Experimental results show that the algorithm bears desirable robustness on geometric attacks.

For the copyright protection of digital video, a new video watermarking algorithm based on 3D-DWT&DCT is proposed. We select video segment and get 3D-DWT&DCT coefficients using 3D-DWT&DCT. The sign sequence of 3DDWT&DCT coefficients is used as feature vector, which is utilized to enhance the robustness against geometrical attacks. Combining the concept of third-party, we describe how to embed and extract the multiple watermarks. Simulation results demonstrate the proposed algorithm has strong robustness to geometrical attacks.

In this paper, the RBF neural network case teaching has been studied. In the actual teaching process, we find it more difficult for student to learn the course, duing to the RBF neural network curriculum theory is more stronger. Many students do not know how to use the theory to solve practical problems.Therefore, we equip students with basic knowledge of RBF neural network through case teaching. In this paper , a RBF neural network example has been analysised and applied to enable the students to learn RBF neural network. Teaching practice shows that case teaching can achieve better teaching effectiveness.

Tourist quantity is an important factor deciding economic benefits and sustainable development of tourism. Thus tourist quantity prediction becomes the important content of tourism development planning. Based on the tourist quantity of Hainan province for more than twenty years, this paper establishes tourist quantity prediction model according to RBF neural network [1], in which the principle and algorithm of RBF neural network is used. And this paper also predicts the future tourist quantity of Hainan province. The Matlab emulational result of RBF neural network model shows based on RBF neural network tourist quantity prediction model can exactly predict the future tourist quantity of Hainan province, thus providing a new idea and mean for tourist quantity prediction.

Different types of the Logistic model are constructed based on a simple assumption that the microbial populations are all composed of homogeneous members and consequently, the condition of design for the initial value of these models has to be rather limited in the case of N(t 0)=N 0. Therefore, these models cannot distinguish the dynamic behavior of the populations possessing the same N 0 from heterogeneous phases. In fact, only a certain ratio of the cells in a population is dividing at any moment during growth progress, termed as θ, and thus, dN / dt not only depends on N, but also on θ. So θ is a necessary element for the condition design of the initial value. Unfortunately, this idea has long been neglected in widely used growth models. However, combining together the two factors (N 0 and θ) into the initial value often leads to the complexity in the mathematical solution. This difficulty can be overcome by using instantaneous rates (V inst) to express growth progress. Previous studies in our laboratory suggested that the V inst curve of the bacterial populations all showed a Guassian function shape and thus, the different growth phases can be reasonably distinguished. In the present study, the Gaussian distribution function was transformed approximately into an analytical form ( $$Y_i = \alpha e^{\left[ { - 0.5\left( {\frac{{x_i - x_0 }}{b}} \right)^2 } \right]} $$ ) that can be conveniently used to evaluate the growth parameters and in this way the intrinsic growth behavior of a bacterial species growing in heterogeneous phases can be estimated. In addition, a new method has been proposed, in this case, the lag period and the double time for a bacterial population can also be reasonably evaluated. This approach proposed could thus be expected to reveal important insight of bacterial population growth. Some aspects in modeling population growth are also discussed.

Using mathematical analysis, a new method has been developed for studying the growth kinetics of bacterial populations in batch culture. First, sampling data were smoothed with the spline interpolation method. Second, the instantaneous rates were derived by numerical differential techniques and finally, the derived data were fitted with the Gaussian function to obtain growth parameters. We named this the Spline-Numerical-Gaussian or SNG method. This method yielded more accurate estimates of the growth rates of bacterial populations and new parameters. It was possible to divide the growth curve into four different but continuous phases based on changes in the instantaneous rates. The four phases are the accelerating growth phase, the constant growth phase, the decelerating growth phase and the declining phase. Total DNA content was measured by flow cytometry and varied depending on the growth phase. The SNG system provides a very powerful tool for describing the kinetics of bacterial population growth. The SNG method avoids the unrealistic assumptions generally used in the traditional growth equations.