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The order of reduction of the MIII/MII redox couple, according to increasing reduction potential, is: [Cr(acac)3] < [Fe(acac)3] < [Mn(acac)3] (with the most positive reduction potential).
The electrochemical data is summarized in Table 1.
Selected electrochemical data and electronic parameters (the acid dissociation constant (pKa), group electron negativities on the Gordy scale (cR + cR' ), Hammett meta substituent constants (σR + σR' ), and the Lever electrochemical ligand parameter (EL)) of [MIII(RCOCHCOR')3] complexes, for M = Cr, Fe or Mn.
b Data from reference [12] c Data from reference [13] d Data from reference [11] e Obtained in dichloromethane Fig. 4.
Data was obtained from references 11, 12 and 13.

Influence of Organic Load on Phosphorous Release and Absorption in HA-A/A-MCO Sludge Reduction Process Jinchao He1,a, Ning Zuo1, b 1Southwestern Science Research Institute of Water Transport Engineering, Chongqing Jiaotong University, Chongqing, 400016, China a401839655@qq.com, bzuoning_2424@126.com Keywords: Sludge Reduction, Phosphorous and Nitrogen Removal, Organic Load, Phosphorous Anaerobic Release, Phosphorous Aerobic Absortion.
Introduction In order to explore the method of improving phosphorous and nitrogen removal in sludge reduction technologies[1], an advanced process combining excess sludge reduction and phosphorous and nitrogen removal is developed, for short, HA-A/A-MCO process (Hydrolysis-Acidogenosis- Anaerobic/Anoxic- Multistep Continuous Oxic tank), which realizes phosphorous removal through hydrolysis acidification of raw sewage and phosphorus-release sludge improving phosphorus-release level and through eliminating anaerobic phosphorous accumulating sewage.
The researching results show that this process has better performance of simultaneous sludge reduction and phosphorous and nitrogen removal.
HA-A/A-MCO is an advanced sludge reduction process which is developed by our research group, whose flow path is shown in Fig.1.
When organic load is 0.141gCOD/gMLSS.d, 0.162gCOD/gMLSS.d and 0.207gCOD/gMLSS.d, the slopes of trio test data can basically coincide with that of regression straight line.

The scheme of the multipath error reduction based on the EMD-Wavelet is suggested.
At last, the scheme of the multipath error reduction are tested and verified by some experiments.
Multipath Error Reduction Model Empirical Mode Decomposition.
We focus on soft-threshold noise reduction model proposed later.
And the data was divided into four different segments (Table 1).

In order to best possible consider the relevant share of geographic location the study uses averaged data.
Therefore, all relevant data is organized and collected.
The phase of the LCI is divided into the steps data collection and calculation.
During data collection an analysis of the production and assembly processes takes place.
The so defined central system flow chart is used as a basis for the following data calculation.

Anaerobic growth of At. ferrooxidans by sulfur reduction.
Isolate CL4 was shown to be mesophilic (data not shown), and was able to grow over a wide pH range (pH 3.0 to 6.5, with an optimum growth pH of ~5).
Stoichiometric precipitation of copper in the off-line traps was, however, less evident, with far less copper being precipitated as CuS than would be expected from ZVI dissolution and proton consumption (data not shown).This was mostly due to the fact that the bioreactor was not air-tight, allowing some to H2S escape.
Subsequent work showed that sulfide genesis also occurred in a non-inoculated bioreactor operated under identical conditions, though rates were smaller than in the At. ferrooxidans reactor (data not shown).
Zerovalent iron, acting as an indirect source of hydrogen in acidic liquors, is also a low-cost energy supply for fuelling sulfur reduction by At. ferrooxidans, and sulfate reduction by aSRB [4].

This study was initially performed via an in-depth analysis of historic production data.
Analysis of Production Data.
Variability existed between the presses in terms of heating capacity and gas delivery system, hence the production data was analysed individually for each press and read-across between the presses was made during post-analysis of the data.
The data gathered from each press was analysed and mapped for each phase of the SPF inflation cycle via the Supported Vector Machine (SVM) data mining approach to establish patterns and correlations between key process variables and process outputs.
The incorporation of interfacial shearing resulted in a significant reduction in sample surface quality with respect to d when compared to the benchmark data (p < 0.05) (Fig. 3).

CO2 Emission Reduction Through a Sustainable Local Suppliers Network of Raw Materials.
Gian Paolo Marino1,a 1Politecnico di Torino, DAD - Department of Architecture and Design, Italy, +39 011 0908828 agianpaolo.marino@polito.it Keywords: CO2 emission reduction, Systemic design, Local potentialities, Sustainable logistic.
Furthermore, these benefits result in a higher quality of the entire supply-chain, in a significant decrease of logistics costs as well as in the consequent reduction of CO2 emissions [2].
In order to go through a project with the SD approach, it is essential to start from the current state of the art and to make a peculiar observation of all the aspects necessary for the system to live (energy and material input) and of what occurs inside it (qualities and quantities data).
Act locally: a) using local materials it is possible to obtain a greater traceability of the resources used in industrial processes so as to ensure, by implication, a high quality finished product; b) reduction of CO2 (actually its production is caused by a supply of raw materials and semi-finished products for packaging manufacturing which happens long away from the points of final packing); c) reduction in energy consumption due to unnecessary transport. 5.

Typical raw data obtained from cone calorimetry are plotted in Figure 1 which shows the evolution of heat given out during combustion of the samples.
Increasing nanoclay concentration clearly improves fire performance as evidenced through a systematic reduction in PHRR.
Cone calorimetry data showing the effect of processing temperature on the nanocomposites.
The PHRR results are detailed in Table 1 which highlights reductions in the order of 27%, 14% and 19% for the samples processed at 240°C, 255°C and 270°C while a reduction in PHRR of 40% was achieved for the samples process at 220°C.
Raw data of burnt samples obtained from cone calorimetry assessment.

Meanwhile, the frequency of one field per second for one target channel, on one hand, ensures that one field is extracted from continuous fifty fields of original video for PAL TV system and the code ratio after compression is 250Kbps, which is 3 percent of the original data size, on the other hand, ensures that one compression channel is available for multiple target channels, which means the reduction of the number of compression chip and cost of the device.
Firstly, the paper proposes the principle of the new television data collection and return technology.
Fig. 1 The television data collection and return technology 1.1 Data collection This television data collection and return technology circularly extracts images from target channels in the cable network, and fulfills the analog-to-digital conversion.
If all the tasks are taken by ARM processor, it can not accomplish the management of other modules. 2.3 Data compression module The data compression technique is accomplished by special compression chip.
References [1] Atmel Corporation: 8-bit AVR Microcontroller Data Sheet (2007.9) [2] Analog Devices: ADV212 JPEG2000 Video Codec Data Sheet Rev.0 (2006) [3] Samsung Electronics: S3C2440A Data Sheet Rev0.13 (2004.2) [4] ASIX Electronics: AX88796 datasheet V1.7 (2007.8) [5] Texas Instruments: TVP5154 Data Sheet (2008)

EBL,historical Annual average historical energy baseline by existing renewable generation units prior to the implementation of the project activity; MWh A minimum of 3 years data is required for calculating the Average of historical energy baseline in this project.
In this paper, we assume that the historical data are available.
So the leakage is not to be considered, LEy=0 Emission Reductions.
Emission reductions are calculated as follows: ERy=BEy- PEy- LEy
Since the distribution of the generation units are dispersive across the whole country, it involves a complex monitoring procedure and high monitoring cost and risks for DOE to validate the data.