Characterization of sintered discs containing distinct sawdust content in the bottom-layer obtained from mercury intrusion porosimetry.Sawdust content (wt.%)Open porosity (%)Bulk density (g/cm3)Median pore diameter (μm)126.96.36.199188.8.131.525.81011.12.1640.8Full-size tableTable optionsView in workspaceDownload as CSVFig. 6. Pore size distribution curves (calculated from mercury intrusion data) for sintered discs produced with distinct sawdust content.Figure optionsDownload full-size imageDownload as PowerPoint slideTo comply with the standard, porcelain stoneware tiles must have bending strength values higher than 35 MPa (ISO 10545/4). In this work, the mechanical resistance of the sintered bi-layered ceramic discs is controlled by the degree of porosity in the bottom-layer of the discs. Fig. 7 presents the bending strength and Young\’s modulus of the fired bodies. Results show that both parameters diminish with increasing sawdust content. Nevertheless, the incorporation of up to 10 wt% of sawdust creates materials that still comply with these specifications. As for other standard properties required for porcelain stoneware tiles they Ro3306 are ensured by the dense top-layer.Fig. 7. Mechanical properties of bi-layered ceramic tiles as a function of sawdust content: (a) bending strength and (b) Young\’s modulus.Figure optionsDownload full-size imageDownload as PowerPoint slideThe specific strength of samples was also evaluated, as proposed by Ashby (2005). Experimental values ranged between 3.2 and 4.0 MPa0.5 cm3/g, being similar to those reported in the literature for lightweight porcelain stoneware tiles (Bernardo et?al., 2010 and Novais et?al., 2014).The creation of porosity in the bottom layer sintered discs is expected to decrease the thermal conductivity of the bodies. In fact, the thermal conductivity strongly decreases with porosity, as shown in Fig. 8. For comparison purposes, the thermal conductivity of a standard ceramic sample (prepared without porogen addition) was included in the figure. A threefold decrease in the thermal conductivity (from 0.71 to 0.23 W/m K) was observed when only 5 wt% sawdust was added to the bottom layer of the bi-layered discs. This observation is consistent with the above-mentioned porogen percolation threshold. Indeed, SEM micrographs in Fig. 5b and f clearly show the formation of networks between adjacent pores, hence reducing the solid paths throughout the ceramic body. The thermal conductivity attenuation with porosity level observed in Fig. 8 was steeper than that observed when polypropylene and polymethyl methacrylate were used as porogen agents (Novais et al., 2014). The thermal insulation achieved with sawdust incorporation endows porcelain stoneware ceramic tiles with new features that may extend the range of applications of this common product.Fig. 8. Thermal conductivity of the porous layer sintered discs, prepared with sawdust, as function of open porosity level. The horizontal line corresponds to the thermal conductivity of a standard composition (without porogen).Figure optionsDownload full-size imageDownload as PowerPoint slide4. ConclusionsThis study evaluated the possibility of using wood wastes (sawdust) as a pore forming agent for producing porcelain stoneware ceramic tiles with novel features.Lightweight bi-layered bodies showing suitable mechanical resistance and low thermal conductivity were fabricated, attesting to the potential of using sawdust as a pore forming agent in such fast-fired ceramic products.Optical microscopy and mercury intrusion porosimetry characterization demonstrated that the porosity level is controlled by sawdust content, and therefore can be tuned considering the application envisaged.Sawdust presents fast and complete combustion, without leaving residues or ashes, and does not induce defects in the ceramics bodies. Additionally, the heat released from its decomposition brings value to the ceramic tile manufacturing process, allowing energy savings.The incorporation of sawdust in the bottom layer of the bi-layered ceramics promotes weight reduction (up to 7.5%) and simultaneous thermal conductivity attenuation (up to 76%). The low porogen percolation threshold (5 wt%) achieved endorsed a threefold decrease in the ceramic tile\’s thermal conductivity in comparison to commercial stoneware tiles. At the same time, the product complies with mechanical strength requirements when sawdust incorporation level is below 10 wt%.Results demonstrate that innovative products with excellent features can be produced by incorporation of sawdust into porcelain stoneware ceramic tiles. The novel ceramic tiles ensure environmental, technical and economic advantages: waste valorisation by sawdust reuse (environmental advantage); density reduction of the product which decreases the tiles transportation and distribution costs (economic advantage); restrain energy loss (technical advantage). These new and exciting features may widen the range of applications of porcelain stoneware tiles while simultaneously contributing towards sustainable construction.AcknowledgementsThe authors acknowledge the financial support from Portuguese Innovation Agency (Adi) through project ThermoCer, to CICECO (PEst C/CTM/LA0011/2013) and RNME – Pole University of Aveiro (FCT Project REDE/1509/RME/2005) for instrument use, scientific and technical assistance. The authors acknowledge CINCA for providing the spray-dried powder, and the assistance of Dr. R.C. Pullar with editing English language in this paper.
Venture capital; Entity industry; Green innovation1. IntroductionAs the important foundation of national economy, entity industry refers to real industry satisfying material and cultural needs of human, including agriculture, manufacturing and most service industries. Entity industry can be divided into green industry and non-green industry from the perspective whether it is conducive to resource conservation and environmental protection. Green industry is conducive to resource conservation and environmental protection. Narrow-sense green industry refers to service industry of GW841819X conservation and environmental management services, while general green industry is the industry consuming less resource and producing less environmental pollution. The so-called non-green industry refers to industries with large consumption of resources and heavy environmental pollution.Green innovation refers to technological innovation that ecological concept is introduced into various stages of technological innovation for entity industry, thus benefiting resource conservation and environmental protection (Zhang, 2013). Practice in developed countries has proved its important supporting role in energy conservation. For example, the use of aeration technology played a huge role in the pollution control project of UK Thames in early 1960s. In 1970s, Japan introduced the world’s most stringent standards of sulfur dioxide emission, greatly reducing sulfur dioxide emissions through desulfurization technology (Bu, 2006).The support of financial industry is indispensable to promote green innovation activities. It is reasonable and necessary for government to provide financial supports due to significant positive externalities of green innovation. However, financial resources form government is very limited compared to the fund demand of green innovation. After all, aspects of response to climate change, pollution control, eco-economy development, and sustainable development are common aspiration of mankind throughout the world. It is the inevitable trend of economic and social development to transform economic development mode and lifestyle with construction of ecological civilization. Thus, expansion of green innovation funding sources has become an inevitable choice for entity industries. According to the prediction of US Energy Foundation and China National Development and Reform Commission, annual financing gap of Chinese energy saving industry, new energy industry and environmental management industry is about 200 billion RMB; it will reach at least two trillion RMB by 2020 (subject group, 2009). Therefore, industries of energy conservation, new energy development and environmental management cannot be promoted for green innovation without active use of financial instruments, thus making it difficult to promote green innovation.Academic research has proved the supporting role of venture capital in technology innovation. Kortum and Lerner (2000) found that venture capital greatly promoted technology innovation in economy in the United States – the promoting effect of 1
Spatial Markov matrix of regional GW841819X efficiency between 1999 and 2010 in China.Spatial lagti/ti+1n1: <75%2: <100%3: <125%4: >125%11200.950.050.000.002120.050.860.090.00340.000.001.000.00400.000.000.000.0021650.900.080.000.022560.050.850.090.013290.000.150.780.074180.000.000.180.8231121.000.000.000.002150.000.690.310.003390.000.190.700.114180.000.050.140.814100.000.000.000.00200.000.000.000.003140.000.000.800.204580.000.000.030.97Full-size tableTable optionsView in workspaceDownload as CSVTable 5 illustrates three factors.First, the spatial relationship between regions plays an important role in the convergence club of energy efficiency in China. With different neighbors, the transition probabilities of regional energy are different. In other words, if the background of a region does not change, the four conditional matrices in the same period in Table 5 should be similar to each other. In fact, the background of a region does not change.Second, different regional backgrounds play different roles in the transfer of energy efficiency type. The probability of an upward shift will increase and the probability of a downward shift will decrease if a region is within the regional neighborhood with a high level of energy efficiency. Conversely, the probability of an upward shift will decrease and the probability of a downward shift will increase if a region is within the regional neighborhood with a low level of energy efficiency. Between 1999 and 2010, when a region with low energy efficiency is adjacent to regions with low energy efficiency, the probability of an upward shift is 5%; meanwhile, if a region is adjacent to regions with medium-low, medium-high, or high-level energy efficiency, the upward shift probability is increased to 8%. The probability of an upward shift is 19%, and the probability of a downward shift is 10% if a region with medium-low energy efficiency is adjacent to regions with low or medium-low energy efficiency; the probability of an upward shift is 31% and the probability of a downward shift is 0% if a region is adjacent to regions with medium-high or high energy efficiency. When a region with medium-high energy efficiency is adjacent to regions with low, medium-low, or medium-high energy efficiency, the probability of an upward shift is 11% and the probability of a downward shift is 34%; meanwhile, if a region is adjacent to regions with high or medium-high energy efficiency, the probability of an upward shift is 20% and the probability of a downward shift is 0%. When a region with high energy efficiency is adjacent to regions with lower energy efficiency, the probability of a downward shift is 32%; meanwhile, if a region is adjacent to regions with higher energy efficiency, the probability of a downward shift is 3%.Third, the matrix of the spatial Markov transition probability provides a spatial interpretation for the “club convergence” phenomenon. A region will be negatively influenced by its geographical neighbors with a low level of energy efficiency. Between 1999 and 2010, if the geographical neighbors of a region have a low level of energy efficiency, the probability of this region to maintain a low level of energy efficiency after several years is 95%. This probability is higher than the probability that ignores the regional neighbors in Table 4, which is 0.92 in the same period. Between 1999 and 2010, the probability of a region to maintain a high level of energy efficiency is 97% if its geographical neighbors are at a high level as well; this probability is higher than the probability in Table 4 in the same period, which is 0.90.4. ConclusionWe adopt DEA in this paper to calculate regional energy efficiency from the perspective of total-factor energy efficiency, and the club convergence of the regional energy efficiency in China is subsequently tested using the Markov chain and spatial Markov chain methods. We draw the following conclusions:(1)The “club convergence” phenomenon exists in the regional energy efficiency in China between 1999 and 2010, and the levels of club convergence are low, medium-low, medium-high, and high. Moreover, the stability of both low- and high-level club convergence is high.(2)The energy efficiency class transitions in China are highly constrained by their regional backgrounds. The regional transitions are positively influenced by regions with a high level of energy efficiency and are negatively influenced by regions with a low level of energy efficiency. These empirical analyses provide a spatial explanation to the existence of the “club convergence” phenomenon of regional energy efficiency in China.(3)In accordance with the dynamic evolution of regional energy efficiency in China, special attention should be paid to spatial effect, and regional cooperation should be strengthened. Policy that favors the “enrich the neighbor” approach should be used in regions with a high level of energy efficiency. Simultaneously considering the geography, population, industry, resources, etc., attains a win–win situation on energy efficiency. Preferential policies should be implemented in the low-level and low-growth regions of energy efficiency to enhance the opening-up level, thus accelerating the adjustment and optimization of the industrial structure, and the promotion of energy efficiency of these areas.AcknowledgementsThis paper is the stage achievement of the National Natural Science Foundation of China (71303029) and the National Social Science Fund Project (10BGL066). The author is grateful for the support of the National Natural Science Foundation of China and the National Social Science Foundation of China.
Fig. 4. Bland–Altman plots representing comparisons between PH797804 laboratory-grade force platform (FP) and the Wii Balance Board (WBB) during STS phase: (A) for the affected side; (B) for the unaffected side; and during RTS phase (C) for the affected side; (D) for the unaffected side. The mean line represents the mean difference between the devices, with the upper and lower lines representing the limits of agreement (two standard deviations).Figure optionsDownload full-size imageDownload high-quality image (546 K)Download as PowerPoint slide
For intra-session reliability, Cronbach\’s alpha revealed excellent agreement for all measures across three trials on the anabolic reactions WBB (0.844–0.995) and the force plates (0.914–0.994) for the STS and RTS phases of the task (Table 2). The agreement of peak force between the first and third trial was also very high when measured by using intra-class correlations. ICC(3,1) values ranged from 0.958 to 0.979 during the STS and RTS phases for the WBB and from 0.963 to 0.986 for the force plates. For the symmetry index; ICC(3,1) ranged from 0.738 to 0.779 for the WBB and from 0.805 to 0.876 on the force plates (Table 2).
Hip flexion/extension and knee flexion/extension were higher in KBM group than in the vacuum group, although only knee flexion/extension for the intact limb revealed significant difference between the groups. Probably, limited sample size prevented those Isoprenaline findings from reaching significance.
Therefore, the use of the vacuum prosthetic fitting reduced some compensations and deviations in transtibial amputees’ gait pattern. This kind of socket enhances suspension of the prosthesis, which improves the forces transference between the stump and the socket , leading to a better prosthesis control.
The MAP revealed different pattern of gait deviation between the groups. Similar to previous studies  and , in KBM group, the major deviations were in hip flexion/extension for the prosthetic limb, knee flexion/extension for the intact limb, knee flexion/extension for the prosthetic limb, ankle dorsi/plantar flexion for the prosthetic limb and hip flexion/extension for the intact limb. The increase of hip flexion/extension for the prosthetic limb may be due to the amputee\’s trend to increase the step length with this limb or due to an anterior position of the trunk, used to enhance the stability during stance . Deviations observed in knee flexion/extension for the prosthetic limb was caused by increased knee extension in mid-stance used to compensate the lack of mobility of the prosthetic foot , and heightened or dampened peak knee flexion during swing  and .
Mean cerebral blood flow (CBF) and transit time at each slice level.Slice levelNumber Afatinib segmentsIMP-CBF [ml/100 g/min]ASL-CBF (default) [ml/100 g/min]ASL-CBF (corrected) [ml/100 g/min]Transit time [ms]Cerebellum2431.3 ± 7.630.6 ± 16.640.0 ± 20.42051.3 ± 347.9Basal ganglia14428.4 ± 5.923.5 ± 11.429.1 ± 15.01874.4 ± 389.8Higher cortex9627.6 ± 5.820.4 ± 9.927.8 ± 13.72113.9 ± 147.9Mean ± S.D.S.D.: standard deviation.Full-size tableTable optionsView in workspaceDownload as CSVFig. 6. Comparison of the cerebral blood flow (CBF) at each slice level.Figure optionsDownload full-size imageDownload high-quality image (124 K)Download as PowerPoint slide(III)Segment-based analysis: Fig. 7 shows the mean CBF in each segment. Segment numbers 16, 17, 21 and 22 showed significant differences between the IMP-CBF and ASL-CBF (default). There were, however, no significant differences between IMP-CBF and ASL-CBF (corrected) in these segments. All other segments showed no significant differences between IMP-CBF and ASL-CBF (default), and IMP-CBF and ASL-CBF (corrected).Fig. 7. Comparison of the cerebral blood flow (CBF) in each segment.Figure optionsDownload full-size imageDownload high-quality image (256 K)Download as PowerPoint slide
Fig. 3. 34 years old, female. CT images show that Ximelagatran the left middle ear is filled with soft tissue components (A). FTS-nEPID reveals a large cholesteatoma as a red-colored area (B, C). This is consistent with operative findings (D, yellow-colored area).Figure optionsDownload full-size imageDownload high-quality image (2094 K)Download as PowerPoint slide
Fig. 4. 25 years old, male. CT images show soft tissue components in the left middle ear (A). FTS-nEPID reveals a small cholesteatoma in both A and TC as a red-colored area (B, C). This is gestation consistent with operative findings (D, yellow-colored area).Figure optionsDownload full-size imageDownload high-quality image (1792 K)Download as PowerPoint slide
Fig. 5. 3 years old, male. CT images show soft tissue components in the left middle ear (A). FTS-nEPID reveals a very small cholesteatoma in TC as a red-colored area (B, C). This is consistent with operative findings (D, yellow-colored area).Figure optionsDownload full-size imageDownload high-quality image (1417 K)Download as PowerPoint slide
Fig. 1. Comparison of cine-MRI, LGE-MRI, and T2 MAP images. (A and B) On CINE-MRI, the endocardial and epicardial borders of the LV wall were delineated semi-automatically on the end-diastolic (A) and end-systolic images (B). LV wall was divided into 60 myocardial sectors by 30 equiangular lines passing through the center of the LV cavity (Argus; Siemens Medical Solutions, Erlangen, Germany) and then the regional contractibility at each sector of the LV wall was automatically calculated as a percentage of the systolic LV wall thickening as follows: systolic LV wall thickening = [(LV wall thicknessES − LV wall thicknessED)/LV wall thicknessED] * 100, where ES and ED SMER 28 end-systole and end-diastole, respectively. Dysfunctional myocardium was defined as sectors with decreased systolic wall thickening lower than 40%. (C) Myocardial infarction was assessed on LGE-MR images. Infarcted myocardium was defined as an area of hyper-enhancement more than five standard deviations (SD) from the remote myocardium. Remote myocardium was defined as non-enhanced myocardium of same size opposite the infarcted myocardium on LGE-MR images. The area of infarcted myocardium (pink area on image) was determined automatically using commercially available MR analysis software after delineating the endocardial and epicardial borders of the LV wall. (D) On T2 map MR images, myocardial edema was defined as myocardium with a T2 value more than 2 SDs higher than Closed reading frame of the remote myocardium. The area of myocardial edema (pink area on image) was determined automatically using commercially available MR analysis software after delineating the endocardial and epicardial borders of the LV wall. (E) The lateral extent of the infarcted myocardium or myocardial edema was calculated as percentage of central angles [(central angle of the involved myocardium/360)*100 (%)].Figure optionsDownload full-size imageDownload high-quality image (757 K)Download as PowerPoint slide
We show that the optimal VENC value for the motion-sensitized driven-equilibrium-balanced magnetic resonance cholangiopancreatography is either 3 or 5 cm/s, which yielded the lowest Cyclophosphamide monohydrate ratios of portal vein/common hepatic duct and liver tissue including visible peripheral vessels/common hepatic duct (Fig. 2) due to better suppression of relative portal vein signals. A lower VENC value (1 cm/s for 3 directions) resulted in higher contrast ratios of portal vein/common hepatic duct, liver tissue including visible peripheral vessels/common hepatic duct and liver tissue excluding visible peripheral vessels/common hepatic duct (Fig. 2). A possible explanation for this result is the common hepatic duct signal suppression due to minimal biliary flow. Because the actual flow velocity of bile has been reported to range from 1.0 to 20.0 mm/s ,  and , the CBD signal suppression at the indicated VENC of 1 cm/s (the effective VENC of 0.58) was thought to be reasonable. Although a significantly better contrast between the biliary system and the liver parenchyma (lower contrast ratios of liver tissue excluding visible peripheral vessels/common hepatic duct) was achieved at a VENC of 9 cm/s (Fig. 2C), VENC values of 7 cm/s and higher resulted in the failure of portal vein signal suppression (Fig. 2A and B), which degrades the diagnostic value of the motion-sensitized driven-equilibrium imaging for magnetic resonance cholangiopancreatography.
Receiver operating characteristic curve (ROC) analysis was used to evaluate the ability of the fitted parameters calculated using different b-value combinations to discriminate PCa with Gleason score of 3 + 3 from those TC-SP 14 with Gleason score of > 3 + 3. Area under the curve (AUC) values were calculated using the trapezoid rule, compared using a modified method  described by Hanley and McNeil . Ninety-five percent confidence intervals for AUC values were calculated using the bootstrapping method and 100 000 samples. Furthermore, Spearman correlation coefficient (ρ) was calculated between the fitted values and Gleason score groups (3 + 3, 3 + 4, > 3 + 4) while 95% confidence intervals for ρ values were estimated by use of the Fisher transformation. In the rest of the manuscript, absolute ρ values are asthma shown. The statistical analyses were performed using in-house written Matlab code (Mathworks Inc., Natick, MA, USA). The Matlab and C++ codes as well as all MR sequences are freely available upon request.
Neither the Framingham risk score (FRS) nor the pooled cohort equation (PCE) ASCVD risk calculators have ever been subjected to clinical trials. However, these Atazanavir 2 risk estimators present no excess expense or clinical harm to patients, and all of the variables needed to calculate the scores are collected as part of routine clinical care. In contrast, CAC represents both an additional expense and a potential harm to the patient (described further below) and, as such, demands a higher level of evidence before widespread implementation.
Finally, the randomized controlled trial (RCT) is considered the apotheosis of evidence-based medicine. Guideline infrastructure, and, hence, best practice, is increasingly driven by RCT evidence; particularly since a 2011 Institute of Medicine report called for developing more trustworthy guidelines (21). While the argument for relying solely on RCT data to inform guidelines is outside the scope of this paper, without a supportive RCT, Degeneracy is unlikely that CAC will attain the level of evidence necessary to inform both changes in clinical practice guidelines and, ultimately, changes in the widespread delivery of preventive cardiac care.
Figure 4. 89Zr-HDL Pharmacokinetics and PET/CT Imaging in Rabbits(A) Blood time-activity curves for 89Zr-AI-HDL (top) and 89Zr-PL-HDL (bottom) in rabbits with atherosclerosis and wild-type control animals (n = 4 per group). (B) Radioactivity distribution in selected P 22077 for 89Zr-AI-HDL (top) and 89Zr-PL-HDL (bottom) at 5 days post-injection (n = 4 per group). (C) PET/CT fusion images of 89Zr-AI-HDL (top) and 89Zr-PL-HDL (bottom) at 1 h, 2 days’, and 5 days’ post-injection in rabbits with atherosclerosis. *p < 0.05. GB = gallbladder; other abbreviations as in Figures 1 and 2.Figure optionsDownload full-size imageDownload high-quality image (787 K)Download as PowerPoint slide
Imaging studies in rabbits
The 89Zr-HDL nanoparticles were evaluated in rabbits by using in vivo PET imaging on a x-ray diffraction clinical PET/CT scanner. Representative PET/CT fusion images of the abdominal region at 3 different time points can be seen in Figure 4C for both nanoparticles. In addition, a unique clinical PET/MRI system was used to investigate the in vivo behavior of the nanoparticles in the same animals and time points for direct comparison. Figure 5A displays representative PET/MRI fusion images of the same animals shown in Figure 4C. The PET images obtained with both scanners were almost identical (Online Video 1). More importantly, there was a strong correlation between the standardized uptake values (SUVs) measured from both systems (Figure 5B) and also excellent agreement between the values (Figure 5C), with an intraclass correlation coefficient of 0.99 (95% confidence interval: 0.98 to 0.99).
Specific caregiver practices that U104 have been associated with higher levels of training are more frequent engagement with children (Bordin, Machida, & Varnell, 2000), less detachment from children (Burchinal et al., 2002), and a greater likelihood for planning of child activities (Kontos, Howes, & Galinsky, 1996). Although these caregiver practices have been shown to promote positive social development in children in center-based child care (e.g., Dunn, 1993; McCartney, Scarr, Phillips, & Grajek, 1985; Peisner-Feinberg et al., 2001), the studies in family child care settings did not directly investigate the impact of Lampbrush chromosomes caregiver practices on children’s behavior. A meta-analysis of caregiver training studies confirms positive impact of caregiver training on caregiver practices in regular child care and preschools, with fewer studies and weaker effects found for children’s skills and behavior (Fukkink & Lont, 2007). These results were found to generalize to child care providers with varying levels of education.