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Fig.1 Roof greening of Tsinghua Fig. 2 Roof vegetable greening of Nanjing Vertical planting can also help energy conservation and emission reduction of buildings while beautifying building through exterior facade structure or independent setting of net, climbing type and net type are used by selected plants(Fig.4).
Fig.5 Plant roots puncture resistant waterproof material test According to detection test data statistics in 2007-2013, there are mainly 6 types of root resistant waterproof materials used for planted roof, namely elastomer (SBS) modified bituminous waterproof sheet material, plastomer (APP) modified bituminous waterproof sheet material, PVC, macromolecule polyethylene polypropylene, thermoplastic polyolefin (TPO) waterproof roll and polyurea.
Only through planning, design, implementation and operation according to the concept of green building and appropriate construction technology integration and large-scale promotion and application can we realize “energy, land, water and material conservation and environmental protection” and achieve the goal of energy conservation and emission reduction.
In 2012, Implementation Opinions of Beijing on Promoting Vertical Planting Construction of Urban Space pointed out, “roof greening is included in green coverage ratio indicator of districts and countries; roof greening included in the indicator of engineering greening land area can enjoy the preference of reduction or exemption of flood prevention charges; water for the maintenance of roof greening is charged according to the charge standard of garden irrigation water and sewage treatment fee is exempted; for newly built/rebuilt medium and high-rise, multi-story and low-rise public buildings without sloping roof with less than 12 floors and a length less than 40m, roof greening must be designed, the area of which shall not be less than 50% of the roof area; for buildings with a floor area over 1000m2, accessible garden roof greening must be set up.
Shanghai, Guangzhou, Chongqing, Chengdu and Wuhan etc. have launched corresponding encouragement policies, regulations, methods and plans to promote the construction and improvement of planted roof of buildings and affiliated facilities and positively promoted orderly implementation of roof greening through reduction or exemption of charges and conversion of greening rate.

Introduction Reduction of the greenhouse pollution, lowering the amount of scrap produced during the fabrication of components and diminishing the number of processing steps are important aspects currently taken into account by the manufacturing sector [1].
Another key feature generally considered during the development and/or improvement of engineered products is the reduction of weight.
The very fine particle size of the Fe/Ni (85-15) powder was chosen in order to favour diffusion of the alloying elements into the Ti matrix as well as the densification of the materials, because a small particle size implies high surface energy which is the driving force for sintering and porosity reduction.
Variation of the density (a) and total residual porosity (b) of the Ti-5.41Fe/Ni and Ti-7.57Fe/Ni alloys versus sintering temperature By comparing the behaviour of the two alloys, it can be noticed that the Ti-7.57Fe/Ni alloy reached higher density, which is due to the combined effect of the intrinsic higher green density of the alloy due to the greater amount of heavy alloying elements and the higher densification due to the higher amount of smaller particles as the porosity (i.e. relative density) data of Fig. 2 b) confirms.
Variation of the hardness of the Ti-5.41Fe/Ni and Ti-7.57Fe/Ni alloys versus sintering temperature As in the case of the density, the hardness of the Ti-5.41Fe/Ni and Ti-7.57Fe/Ni alloys increases with the increment of the sintering temperature as a direct consequence of the reduction of the total residual porosity and homogenisation of the alloying elements.

Based on the order of the limitations, tooling companies can get early access to fixed product information which results in a reduction of the overall development time.
By using a Design Structure Matrix (DSM), the features can be clustered in order to prepare data for the upcoming steps of the method.
The first step is to calculate the cost reduction factor which describes the potential of each feature to reduce the tool costs.
Afterwards, features can be ranked with regard to the severity of the cost reduction factor.
This feature with the highest cost reduction factor needs to be de declared as reference feature which has the biggest impact on the tool costs.

However, because the total reduction during finishing is relatively limited in thick strip, grain refinement may not be fully exploited.
Rolling parameters such as reheat temperature, finishing and coiling temperatures as well as strip reductions and speeds were obtained from mill logs.
Coiling below 625°C, however, resulted in a finer, more acicular ferrite and a significant reduction in pearlite fraction and pearlite colony size, Fig. 7. 0 50 100 150 200 0 0.3 0.6 0.9 1.2 1.5 1.8 Strain Stress, MPa (1090) (1020) (975) (920) (952) (900) (1000) 2 3 4 5 6 7 0 0.2 0.4 0.6 0.8 1 Applied strain below 953 oC (TNR) Ferrite grain size, µµµµm Good industrial DWTT toughness Poor industrial DWTT toughness a)High reheat(1250°C), HT rolling dα =6.3µm b) Low reheat(1150°C), HT rolling dα =5.9µm c) High reheat(1250°C), LT rolling dα =4µm d) Low reheat(1150°C), LT rolling dα =3.9µm Fig. 6.
Shallow, non-energy-absorbing pits were reported to nucleate at cementite particles causing an increase in deformation resistance and a reduction in the ductility limit of the steel.
Thanks go to H. de Klerk for supplying mill data.

The anomalous coarsening of the C11b-phase grains is driven by a reduction in the residual strain on the lamellar interfaces [6].
Such thermal instability of the lamellar microstructure could be significantly improved by the addition of Cr and Zr, that is considered to be due to the reduction in the misfit strain on the lamellar interfaces [13].
These maps were created from the data collected via electron backscatter diffraction (EBSD) of the samples in the scanning electron microscope (SEM).
The results confirm that Cr and Zr additions lead to a significant reduction in the volume fraction of coarse C11b phase grains that do not exhibit a variant orientation relationship, as suggested in Fig. 1.
Reductions in the SSCR owing to refinement of the microstructure have also been reported for directionally solidified eutectic alloys, such as MoSi2/Mo5Si3 [22] and Ni/Ni3Al/Cr3C2 [23], which have aligned microstructures.

In addition, there was no significant biofilm reduction across each of the incubation periods.
Muti-species biofilm formation on polymerized adhesive Time (h) Polymerized adhesive Control 24 0.853 ± 0.02* 1.204 ± 0.051 48 1.166 ± 0.115* 1.786 ± 0.148 72 1.305 ± 0.170* 1.953 ± 0.126 data expressed as mean optical density ± SD * significant difference from a control Fig. 1.
The percentages of multi-species biofilm reduction of cariogenic bacteria on the polymerized adhesive compared with a control Discussion Dental caries is known to be a type of chronic infection of the tooth.
No significant differences in biofilm reduction were observed among the incubation periods.
At 24-h incubation, less biofilm inhibitory effect was demonstrated in this multi-species model (30% vs. 65% biofilm reduction).

First, a lot of calculation data is required considering with the multiple processes of hydrodynamics, sediment transport, water quality and toxics.
It is also found that the reduction of the seawater exchange rate due to construction of tidal power plant made the increase of nutrient salt: nitrogen (1.526ton) and phosphorus (0.102ton).
- Scenario 1(S2.): The reduction of the nutrient salts by 20%
- Scenario 1(S3.): The reduction of the nutrient salts by 50% Figure 4 compares the mass balance of the Scenario 1, 2, and 3.
It is also found that the reduction of the seawater exchange rate due to construction of tidal power plant made the increase of nutrient salt: nitrogen (1.526ton) and phosphorus (0.102ton).

Total inorganic arsenic was determined by the reduction of As (V) to As (III) by the addition of 1 ml of a 25% sodium thiosulphate (Na2S2O3) solution followed by 1 min of shaking.
Reduction of As (V) to As (III) was achieved by the addition of 1 mL of a 25% sodium thiosulphate solution followed by 1 min. shaking.
The determination and quantification of these species need to be done to ensure that the treatment of raw water for public consumption is efficient in the reduction of the level of toxic inorganic species arsenic.
The extensive data collected from about four raw, four pretreated and four treatment (fresh) water samples are given in Table 2.
Water samples taken after the treatment process generally indicated much reduced total inorganic arsenic contents ranging from 50 - 70 % reduction of the original total inorganic arsenic contents.

Therefore, as promising candidates, great potential applications have been researched extensively as oxygen separator [12,13], production of oxygen-enriched carbon dioxide stream [14], membrane reactor for catalytic partial oxidation of methane to syngas [15], oxidative coupling of methane [16], solid oxide fuel cells (SOFC) and new cathode materials for oxygen reduction [17,18].
Teraoka and co-workers [20] reported Fe-based perovskite-type oxides as excellent oxygen-permeable and reduction-tolerant materials.
Their research showed that Fe-based perovskites are more stable against reduction.
According to the data obtained by XRD, compared with the perovskite cubic SrFe0.5Co0.5O3 (JDPDS file No. 46-0335) structure, the SrFexCo0.5O3-δ powders with the Fe content of x=0.5, 0.75, 1.0 are mainly composed of perovskite structure.
Table 1 The weight loss of the SrFexCo0.5O3-δ samples in helium Formula The loss of moisture water The loss of α-oxygen The loss of β-oxygen The loss of p-oxygen t (℃) wt% t (℃) wt% t (℃) wt% t (℃) wt% SrFe0.5Co0.5O3-δ 28.2-297.4 0.34 297.4-554.6 1.96 554.6-751.1 0.13 751.1-898.0 0.21 SrFe0.75Co0.5O3-δ 24.9-308.1 0.28 308.1-760.2 1.86 760.2-821.1 0.50 821.1-898.2 0.10 SrFeCo0.5O3-δ 100.0-320.0 0.37 320.0-742.6 1.41 742.6-873.9 0.66 837.9-897.6 0.17 SrFe1.25Co0.5O3-δ 31.3-321.9 0.38 321.9-737.3 1.44 737.3-898.2 0.43 The α-oxygen is suggested to be accommodated in oxygen vacancies and introduced by the A site substitution, while β-oxygen desorption is ascribable to the reduction of B cations to lower valence [28].

Grey relation clustering and grey whiten weight function clustering are also commonly used in the evaluation of various schemes, but it needs to converse each index into dimensionless, the same level, the positive data which can be added in the application analysis, and the weight is more difficult to be handled [8].
Garage capacity EI1 Comprehensive benefit of car access EI Parking space EI12 Time and efficiency EI2 Development of scenic areas EI3 Carrying capacity EI13 Structural complexity EI14 Equipment flexibility EI15 Equipment cos tEI16 Garage capacity utilization rate EI11 Mechanical equipment running time EI22 Automation degree EI23 Operation of the noise reduction EI31 Surrounding environment of coordination EI32 EI32 Ability of meeting user needs EI33 Efficiency of car access EI21 Management convenience EI34 Technology advanced EI35 Fig.4 Evaluation index system of the stereo parking equipment.
Number Evaluation index Index nature Grey type Inferior Bad Middle Good Excellent 1 Garage capacity utilization rate qualitative 0～0.2 0.2～0.4 0.4～0.6 0.6～0.8 0.8～1 2 Parking space quantitative 3 Carrying capacity qualitative 0～10 10～20 20～30 30～40 40～50 4 Structural complexity qualitative 0～3 3～6 6～9 9～12 12～15 5 Equipment flexibility qualitative 0～0.2 0.2～0.4 0.4～0.6 0.6～0.8 0.8～1 6 Equipment cost qualitative 0～4 4～8 8～12 12～16 16～20 7 Efficiency of car access qualitative 0～0.2 0.2～0.4 0.4～0.6 0.6～0.8 0.8～1 8 Mechanical equipment running time qualitative 0～1.5 1.5～3 3～4.5 4.5～6 6～7.5 9 Automation degree qualitative 0～2 2～4 4～6 6～8 8～10 10 Operation of the noise reduction qualitative 0～3 3～6 6～9 9～12 12～15 11 Surrounding environment of coordination qualitative 0～5.5 5.5～11 11～16.5 16.5～22 22～27.5 12 Ability of meeting user needs qualitative 0～6 6～12 12～18 18～24 24～30 13 Management convenience qualitative 0～5 5～10 10～15 15～20 20～25 14 Technology advanced qualitative 0～4 4～8 8～12 12
Number Evaluation index Index type Design scope System scope 1 Garage capacity utilization rate Larger type Middle Bad Bad Good Good Good 2 Parking space 3～40 3～50 10～140 3～21 10～60 1～6 3 Parking space Larger type Good Middle Good Excellent Middle Middle 4 Structural complexity Smaller type Middle Inferior Middle Inferior Middle Bad 5 Equipment flexibility Larger type Middle Good Middle Good Middle Good 6 Equipment cost Middle type Middle Bad Middle Middle Good Bad 7 Efficiency of car access Larger type Good Good Good Excellent Middle Good 8 Mechanical equipment running time Middle type Bad Inferior Inferior Bad Bad Bad 9 Automation degree Middle type Middle Middle Middle Good Good Middle 10 Operation of the noise reduction Smaller type Bad Bad Middle Inferior Inferior Bad 11 Surrounding environment of coordination Larger type Good Good Middle Excellent Excellent Good 12 Ability of meeting user needs Middle type Middle Good Good Middle Middle Middle 13 Management convenience Middle
Number Evaluation index Information amount of each index 1 Garage capacity utilization rate 3.8074 3.8074 0.8074 0.8074 3.8074 2 Parking space 0.3451 2.1155 0 0.7370 0.7370 3 Parking space 3.3219 1.3219 0.3219 3.3219 3.3219 4 Structural complexity 0.2224 1.8074 0.2224 1.8074 0.8074 5 Equipment flexibility 0.8074 1.8074 0.8074 1.8074 0.8074 6 Equipment cost 2.0000 0 0 2.0000 2.0000 7 Efficiency of car access 1.3219 1.3219 0.3219 3.3219 1.3219 8 Mechanical equipment running time 2.0000 2.0000 0 0 0 9 Automation degree 0 0 2.0000 2.0000 0 10 Operation of the noise reduction 1.3219 3.3219 0.3219 0.3219 1.3219 11 Surrounding environment of coordination 1.3219 3.3219 0.3219 0.3219 1.3219 12 Ability of meeting user needs 2.0000 2.0000 0 0 0 13 Management convenience 0 2.0000 0 0 2.0000 14 Technology advanced 1.8074 0.8074 0.2224 0.8074 3.8074 Total information amount of each scheme I∑ 15.5455 20.2103 3.6032 13.2764 16.4238 From Table 3, it is known that the total information amount of each