Comparison of pH Value, TBA Value, Glycogen and Lactic Acid Content in Muscle of Landrace and Yorkshire under Different Storage Time and Conditions

In order to assess the meat quality under different storage time and conditions, the pH value, TBA value, glycogen and lactic acid content in muscle of Landrace and Yorkshire were measured. The results showed that within 10 h post slaughtering, post slaughtering time had extremely significant influence on pH value and lactic acid content of Landrace, but had no significant influence on glycogen content and TBA value. On the other hand, post slaughtering time had extremely significant influence on pH value of Yorkshire, but had no significant influence on glycogen, lactic acid content and TBA value. The pH values of Yorkshire at 3, 5 and 10 h post slaughtering were 5.21% （ P 〈 0.01 ）, 5.64% （ P 〈 0.05 ） and 5.59% （ P 〈 0.05 ） higher than those of Landrace, respectively ; the lactic acid content in muscle of Landrace at 10 h post slaughtering was 56.04% （P 〈0.05） higher than that of Yorkshire; the TBA value in muscle of Yorkshire at 10 h post slaughtering was 89. 19% （P 〈 0.01 ） higher than that of Landrace; there was no significant difference in glycogen content between Yorkshire and Landrace. When pork stored at 4℃, storage time had no significant influence on pH value and glycogen content in muscle of Landrace, but had significant influence on drip loss, lactic acid content and TBA value ; storage time had no significant influence on pH value, glycogen content and TBA value in muscle of Yorkshire, but extremely significant influence on drip loss and significant influence on lactic acid content. The pH value in muscle of Yorkshire at 24 h post storage at 4℃ was 6.56% （P 〈0.05） higher than that of Landrace; the glycogen contents in muscle of Landrace at 24, 48, 72, 96, 120 and 144 h post storage at 4℃ were 84.90% （P〈0.05）,78.40% （P〈0.01）, 101.87% （P〈0.05）, 83.80% （P〈0.05）, 83.59% （P〈 0.05）and67.25% （P〈0.01）higher than those of York-shire, respectively; the drip loss of Landrace at 72 h post storage and TBA value at 144 h post storage were 55.70% （ P 〈 0.05 ） and 141.33 % （ P 〈 0.01 ） higher than those of Yorkshire, respectively; there was no significant difference in glycogen content between Yorkshire and Landrace. When pork stored at -20℃, storage time had significant influence on TBA value in muscle of Landrace, but had no significant influence on pH value, thawing water loss rate, glycogen and lactic acid content; storage time had no significant impact on pH value, thawing water loss rate, glycogen content and TBA value in muscle of Yorkshire, and had significant influence on lactic acid content. The pH value in muscle of Yorkshire at 24 h post storage at - 20℃ was 5.43 % （ P 〈 0.05 ） higher than that of I.andrace ; the glycogen contents in muscle of Landrace at 24, 48, 72, 96, 120 h post storage at - 20℃ were 85.08% （ P 〈0. 05 ）, 108.66% （ P 〈 0.01 ）, 72.69% （ P 〈 0.05 ）, 90.31% （ P 〈 0.01 ）, 70.38% （ P 〉 0.05 ） higher than those of Yorkshire, respectively ; the thawing water loss rates of Landrace at 24 and 72 h were 160.14% （ P 〈 0.05 ） and 74.32% （ P 〈 0.05 ） higher than those of Yorkshire, respectively ; there was no significant difference in lactic acid content and TBA value at the same time point between Yorkshire and Landrace.

Research on the Summer Drought in Chongqing Using MODIS-EVI Time Series Data

MODIS-EVI time series data from 2000 to 2009 in Chongqing were selected for this study.By the use of best index slope extraction （BISE） method for cloud elimination,analysis on the change vector of EVI time series data were conducted to investigate the EVI response on drought; then,four typical regions were selected to study the relationship between precipitation,temperature and EVI when the sever drought occurred in 2006; finally,based on the time series of vegetation condition index （VCI） and precipitation abnormity percentage,the temporal and spatial distributions of drought were studied.The results showed that,the EVI value of the summer in 2006 was significantly lower than the average EVI at the corresponding period of the other years in Chongqing.In addition,summer drought occurred mainly during the hot and dry weather.Except the southeast area,most of the other regions in Chongqing were all under severe drought.

Probabilistic prediction of expected ground condition and construction time and costs in road tunnels

Ground condition and construction （excavation and support） time and costs are the key factors in decision-making during planning and design phases of a tunnel project. An innovative methodology for probabilistic estimation of ground condition and construction time and costs is proposed, which is an integration of the ground prediction approach based on Markov process, and the time and cost variance analysis based on Monte-Carlo （MC） simulation. The former provides the probabilistic description of ground classification along tunnel alignment according to the geological information revealed from geological profile and boreholes. The latter provides the probabilistic description of the expected construction time and costs for each operation according to the survey feedbacks from experts. Then an engineering application to Hamro tunnel is presented to demonstrate how the ground condition and the construction time and costs are estimated in a probabilistic way. In most items, in order to estimate the data needed for this methodology, a number of questionnaires are distributed among the tunneling experts and finally the mean values of the respondents are applied. These facilitate both the owners and the contractors to be aware of the risk that they should carry before construction, and are useful for both tendering and bidding.

An intelligent automatic correlation method of oilbearing strata based on pattern constraints:An example of accretionary stratigraphy of Shishen 100 block in Shinan Oilfield of Bohai Bay Basin,East China

Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness,an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed.We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata,constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each stratum.The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%,and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results,which is about 17 percentage points higher than that of the existing automatic correlation methods.The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.

Output Feedback Stabilization of an Unstable Wave Equation with Observations Subject to Time Delay

This paper focuses on boundary stabilization of a one-dimensional wave equation with an unstable boundary condition,in which observations are subject to arbitrary fixed time delay.The observability inequality indicates that the open-loop system is observable,based on which the observer and predictor are designed:The state of system is estimated with available observation and then predicted without observation.After that equivalently the authors transform the original system to the well-posed and exponentially stable system by backstepping method.The equivalent system together with the design of observer and predictor give the estimated output feedback.It is shown that the closed-loop system is exponentially stable.Numerical simulations are presented to illustrate the effect of the stabilizing controller.

LEARNING MULTIVARIATE TIME SERIES CAUSAL GRAPHS BASED ON CONDITIONAL MUTUAL INFORMATION

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis.This paper provides a method that employs both mutual information and conditional mutual information to identify the causal structure of multivariate time series causal graphical models.A three-step procedure is developed to learn the contemporaneous and the lagged causal relationships of time series causal graphs.Contrary to conventional constraint-based algorithm, the proposed algorithm does not involve any special kinds of distribution and is nonparametric.These properties are especially appealing for inference of time series causal graphs when the prior knowledge about the data model is not available.Simulations and case analysis demonstrate the effectiveness of the method.

Variational Formulation of 1-D Unsteady Compressible Flow in a Deforming Tube

The variational principles for 1-D unsteady compressible flow in a deforming tube derived in a previous paper are improved essentially by reconstructing the initial/final-integral terms according to a new method suggested in a recent paper. As a result, the inherent shortcoming of variational principles of being unable to admit physically rational initial/final-value conditions in initial/boundary-value problems is successfully eliminated. Thus, a new theoretical basis for the time-space finite-element analysis is provided.

The dynamic response of forest vegetation to hydro- thermal conditions in the Funiu Mountains of western Henan Province

This paper uses HJ-1 satellite multi-spectral and multi-temporal data to extract forest vegetation information in the Funiu Mountain region. The S-G filtering algorithm was employed to reconstruct the MODIS EVI（Enhanced Vegetation Index） time-series data for the period of 2000–2013, and these data were correlated with air temperature and precipitation data to explore the responses of forest vegetation to hydrothermal conditions. The results showed that：（1） the Funiu Mountain region has relatively high and increasing forest coverage with an average EVI of 0.48 over the study period, and the EVI first shows a decreasing trend with increased elevation below 200 m, then an increasing trend from 200–1700 m, and finally a decreasing trend above 1700 m. However, obvious differences could be identified in the responses of different forest vegetation types to climate change. Broad-leaf deciduous forest, being the dominant forest type in the region, had the most significant EVI increase.（2） Temperature in the region showed an increasing trend over the 14 years of the study with an anomaly increasing rate of 0.27℃/10a; a fluctuating yet increasing trend could be identified for the precipitation anomaly percentage.（3） Among all vegetation types, the evergreen broad-leaf forest has the closest EVI-temperature correlation, whereas the mixed evergreen and deciduous forest has the weakest. Almost all forest types showed a weak negative EVI-precipitation correlation, except the mixed evergreen and deciduous forest with a weak positive correlation.（4） There is a slight delay in forest vegetation responses to air temperature and precipitation, with half a month only for limited areas of the mixed evergreen and deciduous forest.