区域旅游产业发展潜力测评及显化机制分析

本文通过分析旅游产业发展潜力的构成,构建了旅游市场需求拉动力分析模型。应用主成分因子分析法,对我国省级区域的旅游市场需求进行了有效测评,而后根据旅游需求市场相关资料对31个省份进行了综合测评,揭示了各省旅游业发展潜能和潜在优、劣势。基于定量测评结果,结合产业竞争力相关理论、我国旅游产业发展的内在规律以及外部环境影响,有效地阐述了旅游产业发展显化的内在推动原理,将各种影响因子整合成显化机制,有效地将旅游产业的内在潜力发展成为现实的区域竞争力,希望本文的研究可以为区域旅游产业的发展提供一定的理论与实践指导意义。

Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis:A Bidirectional Mendelian Randomization Study

Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization(MR) analysis.Methods Bidirectional MR was used to analyze pooled data from different genome-wide association studies(GWAS). The causal effect of plasma metabolites on osteoporosis was estimated using the inverse variance weighted method, intersections of statistically significant metabolites obtained from different sources of osteoporosis-related GWAS aggregated data was determined, and then sensitivity analysis was performed on these metabolites. Heterogeneity between single nucleotide polymorphisms was evaluated by Cochran's Q test. Horizontal pleiotropy was assessed through the application of the MR-Egger intercept method and the MRPRESSO method. The causal effect of osteoporosis on plasma metabolites was also evaluated using the inverse variance weighted method. Additionally, pathway analysis was conducted to identify potential metabolic pathways involved in the regulation of osteoporosis.Results Primary analysis and sensitivity analysis showed that 77 and 61 plasma metabolites had a causal relationship with osteoporosis from the GWAS data in the GCST90038656 and GCST90044600 datasets, respectively. Five common metabolites were identified via intersection. X-13684 levels and the glucose-to-maltose ratio were negatively associated with osteoporosis, whereas glycoursodeoxycholate levels and arachidoylcarnitine(C20) levels were positively associated with osteoporosis(all P < 0.05). The relationship between X-11299 levels and osteoporosis showed contradictory results(all P < 0.05). Pathway analysis indicated that glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, galactose metabolism, arginine biosynthesis, and starch and sucrose metabolism pathways were participated in the development of osteoporosis.Conclusion We found a causal relationship between plasma metabolites and osteoporosis. These results offer novel perspectives with important implications for targeted metabolite-focused interventions in the management of osteoporosis.

Reduction of distortion and improvement of efficiency for gridding of scattered gravity and magnetic data

This paper presents a reasonable gridding-parameters extraction method for setting the optimal interpolation nodes in the gridding of scattered observed data. The method can extract optimized gridding parameters based on the distribution of features in raw data. Modeling analysis proves that distortion caused by gridding can be greatly reduced when using such parameters. We also present some improved technical measures that use human- machine interaction and multi-thread parallel technology to solve inadequacies in traditional gridding software. On the basis of these methods, we have developed software that can be used to grid scattered data using a graphic interface. Finally, a comparison of different gridding parameters on field magnetic data from Ji Lin Province, North China demonstrates the superiority of the proposed method in eliminating the distortions and enhancing gridding efficiency.

Dynamic Analysis on Organic Matter and Nitrogen Pollution of Dongchang Lake

The aim was to explore dynamic changes of organic matter and nitrogen pol ution in Dongchang Lake. [Method] Monitoring data, including BOD5, CODCr, NH3-N and TN, of Dongchang Lake were chosen for analysis during 2002-2011. [Result] Water quality of the six lake districts showed deteriorating in monitor-ing period, and TN was the dominant pol ution factor; BOD5/CODCr ratio was low, suggesting biodegradability of organic pol utant in the lake was lower. NH3/TN ratio was higher, indicating NH3-N was a major factor causing nitrogen exceeding in 2010. In addition, correlations between BOD5 and CODCr and between NH3-N and TN in the lake districts maintained at a significant level. [Conclusion] The research provides references for improving water in Dongchang Lake.

Changes of Labile Organic Carbon Fractions in Soils Under Different Rotation Systems

Soil labile (biologically active) organic carbon fractions under different crop rotation systems in Jiangsu Province, China, were investigated after 10 years of rotation. The rotation systems, including green manurerice-rice (GmRR), wheat-rice-rice (WRR), wheat-rice (WR) and wheat/corn intercrop-rice (WCR) rotations,were established on paddy soils using a randomized complete block design with three replicates. The total organic carbon (TOC), total nitrogen (TN) and water-soluble organic carbon (WSOC) in the soils under different systems were greater in the GmRR and WRR than in the WR and WCR rotation systems because the soils under triple cropping often received more crop residues than the soils under double cropping. Both the WSOC and the microbial biomass carbon (MBC) contents in the soils of the GmRR rotation system were significantly greater than those in the other crop rotation systems, which was due to the return of green manure to the fields of the GmRR rotation system. The results of a 13C nuclear magnetic resonance (13C-NMR) analysis indicated that the structural characteristics of soil WSOC were similar under the four crop rotation systems with carbohydrates and long-chain aliphatics being the major components. Correlation analysis showed that the content of the WSOC was positively correlated with that of the MBC (P ＜0.01),and all had significantly positive correlations with TOC and TN. The coefficients of variation (CVs) for WSOC and WSOC/TOC were greater than the other indices (e.g, MBC, TOC and TN), suggesting that WSOC in the soils was more sensitive to these rotation systems. The results above indicated that the soil amended with green manure could not only increase the usable C source for soil microorganisms, but could also enhance soil organic matter content; hence, rotation with green manure would be a good strategy for sustainable agriculture.

The quantified analysis of China's GM cotton yield capacity by C-D function and stochastic frontier model

Using a modified C D function and stochastic frontier model, the paper analyzed China's cotton yield capacity and found that the yield and technical efficiency of China's cotton planting system can be increased by the use of genetically modified (GM) varieties.

Mechanism analysis and process optimization of sand and plug removal with rotating jet in horizontal well

In the view of the problems existing in horizontal well,such as sand depositing and cleaning difficulty of borehole,a technology with rotating jet suitable to resolution of the problems was presented.Based on liquid solid two-phase flow theory,the analyses on the sand movement law and the swirling field influential factors were conducted.Results show that:1) With the increasing of displacement in horizontal section annulus,swirling field strength increases,and when the displacement is constant,the closer from the nozzle,the stronger the swirling field strength is;2) Head rotating speed and liquid viscosity have little influence on the swirling field strength,but the sand-carrying rate of fluid can increase by increasing liquid viscosity in a certain range;3) Rotating the string and reducing its eccentricity in annulus are conducive for sand migration in the annulus;4) The sand can be suspended and accelerated again and the swirling field strength is enhanced by the helix agitator.Hence,the research results provide the theoretical basis for the design and application of rotating jet tool.

θ-PSO: a new strategy of particle swarm optimization

Particle swarm optimization (PSO) is an efficient, robust and simple optimization algorithm. Most studies are mainly concentrated on better understanding of the standard PSO control parameters, such as acceleration coefficients, etc. In this paper, a more simple strategy of PSO algorithm called θ-PSO is proposed. In θ-PSO, an increment of phase angle vector replaces the increment of velocity vector and the positions are decided by the mapping of phase angles. Benchmark testing of nonlinear func- tions is described and the results show that the performance of θ-PSO is much more effective than that of the standard PSO.

Relationships Between Agronomic and Environmental Soil Test Phosphorus in Three Typical Cultivated Soils in China

A study was conducted to determine the relationships between agronomic soil test P and environmental soil test P in three soils predominately distributing in three typical agricultural production areas of China. Soil P was analyzed using Bray-1 （BP）, Olsen （OP）, and Mehlich-3 （MP） methods as agronomic tests, and using Fe-oxide impregnated filter paper （FeP）, anion-exchange resin membrane （RP）, and water （WP） as environmental tests. There were linear relationships between soil P extractable with all the tests evaluated. The regression coefficients, R^2, ranged from 0.8164 to 0.9409 between each two of the agronomic soil test P, and ranged from 0.4702 to 0.8990 between each two of the environmental soil test P, when the three soils were considered separately. When soil test P was analyzed across all the three soils, the highest regression R^2 was found between OP and MP （0.7940） amongst agronomic soil test P, and between FeP and RP amongst environmental soil test P （0.8842）. While all of the three agronomic soil test P was linearly related to each of the environmental soil test P across the three soils, strongest relationships were found between OP and environmental soil test P. Agronomic OP may be adopted as an analytical tool for environmental prediction of soil P.

Homogeneity Analysis of Multiairport System Based on Airport Attributed Network Representation Learning

The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system from the perspective of route network analysis,and the attribute information of airport nodes in the airport route network is not appropriately integrated into the airport network.In order to solve this problem,a multi-airport system homogeneity analysis method based on airport attribute network representation learning is proposed.Firstly,the route network of a multi-airport system with attribute information is constructed.If there are flights between airports,an edge is added between airports,and regional attribute information is added for each airport node.Secondly,the airport attributes and the airport network vector are represented respectively.The airport attributes and the airport network vector are embedded into the unified airport representation vector space by the network representation learning method,and then the airport vector integrating the airport attributes and the airport network characteristics is obtained.By calculating the similarity of the airport vectors,it is convenient to calculate the degree of homogeneity between airports and the homogeneity of the multi-airport system.The experimental results on the Beijing-Tianjin-Hebei multi-airport system show that,compared with other existing algorithms,the homogeneity analysis method based on attributed network representation learning can get more consistent results with the current situation of Beijing-Tianjin-Hebei multi-airport system.

Mechanism Design and Motion Analysis of Heavy⁃Load Transfer Robot with Parallel Four⁃Bar Mechanism

Heavy-load transfer robots are widely used in automobile production and machinery manufacturing to improve production efficiency.In order to meet the needs of large billet transfer,a 4-DOF transfer robot is designed in this paper,which consists of parallel four-bar mechanisms.The Jacobian matrix referring to the mapping matrix from the joint velocity to the operating space velocity of the transfer robot can be solved by the differential-vector method.The mean value of the Jacobian matrix condition number in the workspace is used as the global performance index of the robot velocity and the optimization goal.The constraint condition is established based on the actual working condition.Then the linkage length optimization is carried out to decrease the length of the linkage and to increase the global performance index of velocity.The total length of robot rods is reduced by 6.12%.The global performance index of velocity is improved by 45.15%.Taking the optimized rod length as the mechanism parameter,the distribution of the motion space of the transfer robot is obtained.Finally,the results show that the proposed method for establishing the Jacobian matrix of the lower-mobility robot and for the optimization of the rods based on the velocity global performance index is accurate and effective.The workspace distribution of the robot meets the design requirements.

Effect of Sn on synthesis of nanocrystalline Ti-based alloy with fcc structure

The effect of the amount of Sn on the formation of fcc phase in Ti-13 Ta-x Sn(x=3,6,9 and 12,at.%)alloys was studied.The alloys were synthesized by mechanical alloying using a planetary mill,jar and balls of stabilized yttrium.Using Rietveld refinement,it was found that the obtained fcc phase has crystallite size smaller than 10 nm and microstrain larger than 10-3.Both conditions are required to form an fcc phase in Ti-based alloys.For all samples,the microstructure of the fcc phase consists of equiaxial crystallites with sizes smaller than 10 nm.The largest presence of fcc phase in the studied Ti alloy was found with 6 at.%Sn,because this alloy exhibits the largest microstrain(1.5×10-2)and crystallite size of 6.5 nm.Experimental data reveal that a solid solution and an amorphous phase were formed during milling.The necessary conditions to promote the formation of solid solution and amorphous phases were determined using thermodynamic calculations.When the amount of Sn increases,the energy required to form an amorphous phase varies from approximately 10 to approximately-5 k J/mol for 3 and 12 at.%Sn,respectively.The thermodynamic calculations are in agreement with XRD patterns analysis and HRTEM results.

Significance of Transients in Soil Temperature Series

The primary objective of this study was to investigate the impact of observation scale on the estimation of soil thermal properties.Transients are usually filtered out and ignored when classical Fourier approaches are used to deconstruct and model temperature time series.It was hypothesized that examination of such transients may be more important in identifying and quantifying short-term perturbations in internal soil heat transfer induced by agronomic disturbances. Data-logged temperatures were collected at 10-minute intervals from thermistor probes installed at 10 and 25 cm depths in isolated areas of two grassed plots.One plot(6T)had been treated twice with 6 Mg ha^(-1)composted turkey litter as received.The other plot(NPK)was fertilized at the same time with NPK fertilizer.Various methods were used to analyze the series to obtain apparent soil thermal diffusivity(D-value)at various time scales.Results supported the hypothesis that short-term differences in internal soil heat transfer between the 6T and NPK plots were more manifest and effectively captured by estimated D-values calculated from the monthly and daily partial series.The 6T plot had higher soil organic matter content than the NPK plot and had lower apparent soil thermal diffusivity.Diurnal soil temperature amplitudes, required to calculate the mean D-values from partial series,were more effectively obtained using a temperature change rate method.The more commonly used Fourier analysis tended to be effective for this purpose when the partial series reasonably presented well-defined diurnal patterns of increasing and decreasing temperatures.

Exponential synchronization of general chaotic delayed neural networks via hybrid feedback

This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model,which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator,and covers several well-known neural networks,such as Hopfield neural networks,cellular neural networks(CNNs),bidirectional associative memory(BAM)networks,recurrent multilayer perceptrons(RMLPs).By virtue of Lyapunov-Krasovskii stability theory and linear matrix inequality(LMI)technique,some exponential synchronization criteria are derived.Using the drive-response concept,hybrid feedback controllers are designed to synchronize two identical chaotic neural networks based on those synchronization criteria.Finally,detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Sentiment classification model for bullet screen based on self-attention mechanism

With the development of short video industry,video and bullet screen have become important ways to spread public opinions.Public attitudes can be timely obtained through emotional analysis on bullet screen,which can also reduce difficulties in management of online public opinions.A convolutional neural network model based on multi-head attention is proposed to solve the problem of how to effectively model relations among words and identify key words in emotion classification tasks with short text contents and lack of complete context information.Firstly,encode word positions so that order information of input sequences can be used by the model.Secondly,use a multi-head attention mechanism to obtain semantic expressions in different subspaces,effectively capture internal relevance and enhance dependent relationships among words,as well as highlight emotional weights of key emotional words.Then a dilated convolution is used to increase the receptive field and extract more features.On this basis,the above multi-attention mechanism is combined with a convolutional neural network to model and analyze the seven emotional categories of bullet screens.Testing from perspectives of model and dataset,experimental results can validate effectiveness of our approach.Finally,emotions of bullet screens are visualized to provide data supports for hot event controls and other fields.

Structural characterization of coconut tree leaf sheath fiber reinforce-ment

The coconut palm tree leaf sheath fibers were analyzed by FTIR spectral analysis, Chemical, X-ray and thermo gravimetric methods to assess their suitability as reinforcements in the preparation of green composites. The morphology of the untreated and alkali treated fibers was studied by scanning electron microscopic method. The FTIR and chemical analyses indicated lowering of hemi-cellulose content by alkali treatment of the fibers. The X-ray diffraction revealed an increase in crystallinity of the fibers on alkali treatment. The thermal stability of the fibers was found to increase slightly by alkali treatment. The tensile properties of these fibers increased on alkali treatment. The mechanical and other physical properties indicated that these fibers were suitable as reinforcements for making the green composites.

Energy analysis of mechanical alloying of molybdenum disilicide in a new-type high energy vibrating ball mill

In order to understand the fundamentals of a high energy vibrating type milling process, the energy transfer during me-chanical alloying of molybdenum disilicide is investigated based on the Magini-Iasonna energy transfer method, amended by Murty. The efficiency factor and total energy of milling are calculated. MoSi2 synthesized by a mechanically induced self-propagating reaction has also been studied according to different milling parameters, such as the number of balls and the ball to powder weight ratio. The results indicate that the efficiency factor is between 1.944 and 8.507 J/(g·s). A total milling energy of about 19.38–26.47 kJ/g is found to be necessary for the mechanically induced self-propagating reaction of a Mo:2Si powder mixture. The efficiency of milling energy transfer is about 3.3%–4.5%. The experiment and modeling show that the optimum condition for mechanical alloy-ing is a half full vial of balls.

Carbon dioxide insufflation during colonoscopy in deeply sedated patients

AIM:To compare the impact of carbon dioxide(CO2) and air insufflation on patient tolerance/safety in deeply sedated patients undergoing colonoscopy.METHODS:Patients referred for colonoscopy were randomized to receive either CO2 or air insufflation during the procedure.Both the colonoscopist and patient were blinded to the type of gas used.During the procedure,insertion and withdrawal times,caecal intubationrates,total sedation given and capnography readings were recorded.The level of sedation and magnitude of patient discomfort during the procedure was assessed by a nurse using a visual analogue scale(VAS)(0-3).Patients then graded their level of discomfort and abdominal bloating using a similar VAS.Complications during and after the procedure were recorded.RESULTS:A total of 142 patients were randomized with 72 in the air arm and 70 in the CO2 arm.Mean age between the two study groups were similar.Insertion time to the caecum was quicker in the CO2 group at 7.3 min vs 9.9 min with air(P = 0.0083).The average withdrawal times were not significantly different between the two groups.Caecal intubation rates were 94.4% and 100% in the air and CO2 groups respectively(P = 0.012).The level of discomfort assessed by the nurse was 0.69(air) and 0.39(CO2)(P = 0.0155) and by the patient 0.82(air) and 0.46(CO2)(P = 0.0228).The level of abdominal bloating was 0.97(air) and 0.36(CO2)(P = 0.001).Capnography readings trended to be higher in the CO2 group at the commencement,caecal intubation,and conclusion of the procedure,even though this was not significantly different when compared to readings obtained during air insufflation.There were no complications in both arms.CONCLUSION:CO2 insufflation during colonoscopy is more efficacious than air,allowing quicker and better cecal intubation rates.Abdominal discomfort and bloating were significantly less with CO2 insufflation.

Identification of indoor multi-component pollution gas aliasing peak based on JADE

Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction method based on joint approximative diagonalization of eigenmatrix（JADE）is proposed.By fully mining the hidden information of original data and analyzing higher-order statistics information of the data,each substance spectrum in the mixed gas can be accurately distinguished.In addition,a multi-dimensional data quantitative analysis model of the extracted independent source is established by using support vector machine（SVM）based on regular theory.The experimental results show that the correlation coefficients of the components of mixed gases is above 0.999 1by quantitative analysis,which verifies the accuracy of this feature extraction method.