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)220.127.116.1118.104.22.1685.81011.12.1640.8Full-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.
This procedure is based on the creation of an a priori set of discrete values (εUL(1),εUL(2),…,εUL(n)) within the required range. Introducing these A 967079 values into the model gives the corresponding sets for εCL, εCR and εUR. These sets describe the relations between the axial and the compressive strain for given beam geometry and the material properties for the ideal and the damaged beam. Having the measured values of the axial strain εU, the compressive strain εC can be estimated from the expressionsequation(27)εC=εCL(i+1)−εCL(i)εUL(i+1)−εUL(i)(εU−εUL(i))+εCL(i)and for the initially ideal beam andequation(28)εC=εCR(i+1)−εCR(i)εUR(i+1)−εUR(i)(εU−εUR(i))+εCR(i)for the initially damaged beam. The indices i+1 and i denote the interval in which the value of εU is diversity placed. Number of points in the a priori sets is not limited so the ‘discretization’ can represent the original curves very precisely. The measured values of εU are then inserted into the discretized model and the corresponding values of εC are calculated. Both values are then used in calculation of the corresponding beam deflection D which can be input into Eq. (7).
For visualization, although the 0° endoscope provides an excellent view of the planum sphenoidale and the 30° endoscope provides an excellent view of the anterior skull base, the 45° endoscope allows the most optimal view through the frontal sinus corridor provided by the Draf III procedure.13 The 70° endoscope can be used to expand the field of view further but can be very difficult to use for guiding surgical instruments because it GR 79236 results in the greatest distortion of the two-dimensional view. For this reason, it was not used in this study. The acute angle between the anterior portion of the nostrils and the frontal sinus also represents an anatomic limitation to surgical manipulation inside the frontal sinus cavity under direct visual control.
Our cadaveric results are similar to previously reported measurements of 33.7 mm (range, 29–40 mm) in the anteroposterior direction (posterior wall of frontal sinus to planum sphenoidale) and 23.5 mm (range, 20–27 mm) and 19.1 mm (range, 17–22 mm) in the transverse direction (orbit to orbit) at the level of the anterior ethmoidal artery and posterior ethmoidal artery, respectively.13 The differences Permian Period we have reported in the radiographic and cadaveric measurements are likely due to the slight subjectivity in which slice on the CT scanner is used for the measurement; however, our measurements did fit within the standard error.
We present a case of PPTID in a young adult, who was managed with a multidisciplinary approach. Histopathologic, cytogenetic, and mutational profiling revealed several alterations that may be significant to PPT pathogenesis and diagnosis. No widely accepted treatment course has been determined for PPTIDs. However, based on this VER 155008 case and our review of the literature, we advocate for initial resection of the tumor to the maximal extent permitted without compromising neurologic function and adjuvant chemoradiation for residual or recurrent disease.
AICA, Anterior inferior cerebellar artery; CCA, Common carotid artery; COSS, Carotid Occlusion Surgery Study; CTA, Computerized tomographic angiography; EC-IC, External carotid to internal carotid artery; JET, Japanese EC-IC Bypass Trial; mRS, Modified Rankin scale; OA, Occipital artery; P2, Second segment of the osmotic pressure posterior cerebral artery; PCA, Posterior cerebral artery; PICA, Posterior inferior cerebellar artery; PTAS, Percutaneous transluminal angioplasty and stenting; SAMMPRIS, Stenting and Aggressive Medical Management for Preventing Recurrent stroke in Intracranial Stenosis; SCA, Superior cerebellar artery; STA, Superficial temporal artery; TIA, Transient ischemic attack; VBI, Vertebrobasilar ischemia
2.2.1. Fröhlich and the modified representation
The three parameters in the modified Fröhlich equation, can be seen in Fig. 14, Fig. 15, Fig. 16, Fig. 17, Fig. 18, Fig. 19, Fig. 20 and Fig. 21 for all the measured materials from . They all represent the measured B-H curves and have been fitted in a least square sense. The fitting of the modified Fröhlich and the original Fröhlich equations can be seen in Fig. 1, and it Perifosine shows a better fitting with the modified Fröhlich equation as expected. Further explanation of big bang theory is given in Section 3.
Fig. 1. Example B-H curve measured showed together with best fit to the Fröhlich and the modified Fröhlich equation.Figure optionsDownload full-size imageDownload as PowerPoint slide
The two co-energies should give an over and underestimation of the heat losses, respectively. These values are subsequently used to calculate a fictitious linear material with a relative permeability of:equation(16)μrif=w1i+w2iμ0(Hmif)2
Average AIF-EMM parameters and goodness P 22077 fit (R2), and their standard deviations (s.d.) and coefficients of variations (CV) for AIFLD (n = 22).A (mM)β (min− 1)A1σ1 (min)t1 (min)A2σ2 (min)t2 (min)R2Average0.310.705.840.090.200.460.120.620.95s.d.0.140.152.470.030.080.240.080.090.02CV0.440.220.420.380.400.520.650.150.02Full-size tableTable optionsView in workspaceDownload as CSV
Average EMM parameters and goodness of fit (R2), and their standard deviations (S.D.) and coefficients of variations (CV) for AIFSD (n = 22).A (mM)α (min− 1)γ (min− 1)R2Average0.368.930.610.93s.d.0.125.400.480.09CV0.320.610.800.09Full-size tableTable optionsView in workspaceDownload as CSV
Fig. 3. Plots of AIFLD (red line), AIFSD (black line), and AIFref (green line) derived from muscle reference tissue are positive feedback control shown for a representative subject. AIFLD was scaled by the MR-measured concentration ratio in the washout portions.Figure optionsDownload full-size imageDownload high-quality image (170 K)Download as PowerPoint slide
Fig. 2. Phantom MRE Wave Images.A) One offset of the acquired wave data in the phantom. B, C) The forward and reflected waves isolated using Sanguinarine Chloride 1D directional filter.Figure optionsDownload full-size imageDownload high-quality image (57 K)Download as PowerPoint slide
2.2. Ex vivo porcine aorta
4 ex vivo porcine aortas were obtained from seven-month-old male domestic healthy pigs (100–130 kg) within 15 min of slaughter from a local commercial slaughterhouse. The aortas were immersed in 0.9% saline solution (0.9% sodium chloride USP pH 5.0 (4.5 to 7.0) mEq/L solidum 154 chloride 154 osmolarity 308 mOsmol/L, Baxter Healthcare, IL, USA) and preserved at room temperature prior to examination. All the side branches were tied off. Fig. 3 shows a picture of one of the excised porcine aortas.
Fig. 3. Excised porcine aorta.Figure optionsDownload full-size imageDownload high-quality image (278 K)Download as PowerPoint slide
The porcine aortas were cut to about 28 cm in length and were embedded in 10% B-gel as was done for the phantom study described above. 3 aortas were embedded in a single gel, and the other aorta used for control was embedded in another gel phantom. Glass rod was placed in each aortic lumen before being embedded in the hot gel to prevent the collapse due to the weight; when the B-gel cooled down and solidified, the glass rod was removed from the aortic lumen for MRE experiments. MRE was performed on each porcine aorta with the same driver arrangement and MRE protocol as the phantom study. Similar to the phantom study, tap water was circulated through the aortas during the scans. The total time from death of the animal to completion of all examinations on the aortas was approximately 12 h.
AcknowledgementsThis study was supported by Guerbet Korea. And we’d like to appreciate to Jong Han Yu, M.D., Hee Jeong Kim, M.D., and Beom Seok Ko, M.D., breast surgeons of our institution for their kind contribution.
Ultrashort echo time; Magnetic resonance imaging; Knee; Meniscus
Magnetic resonance image (MRI) provides a good KN-93 between the different soft tissues of the body, which makes it especially useful for musculoskeletal imaging. However, the capabilities of MRI are limited for use on musculoskeletal tissues such as ligaments, tendon, meniscus, and bone, which contain a majority of the short T2 time constants , ,  and ; there is little or no signal obtained from these tissues when using conventional MRI techniques.
Meniscal degeneration and tearing are well-known cofactors in the pathogenesis of osteoarthritis . To evaluate these meniscal pathologies, elevations of ultrashort-T2* values are important, even in patients with subclinical meniscus degeneration ,  and . The ultrashort echo time (TE) sequence allows MRI to be applied to these short T2 tissues.
The largest randomized clinical trial of SCS in HF, the DEFEAT-HF (Determining the Feasibility of Spinal Cord Neuromodulation for the Treatment of Chronic Heart Failure) randomized controlled study was completed recently (36). DEFEAT-HF enrolled 81 patients with NYHA functional class III HF and a mean LVEF of 29 ± 5%, with 66 successfully randomized and implanted with the SCS device system. All of the patients were implanted with a SCS device that Glyoxalase I consisted of a single 8-electrode lead in the epidural space. The electrode was connected to an SCS stimulator, which was placed subcutaneously in the lateral abdominal wall. Stimulation electrodes were placed to encompass the T2 to T4 levels. Patients were randomized 3:2 to SCS or OMT (control) for 6 months; after 6 months, the control patients were crossed over to the active therapy arm and 12-month data were collected in both randomization arms. The stimulation in the treatment group was programmed on for 12 h a day, on the basis of individual sleep/wake cycles, at a stimulation frequency of 50 Hz, 200 ms pulse duration, and output set at 90% maximum tolerated voltage determined while sitting. The primary study endpoint was a reduction in the LV end-systolic volume index after 6 months of SCS therapy in the treatment arm versus the control arm. Secondary outcomes included change in peak O2 consumption and change in NT-proBNP at 6 months. The results of the DEFEAT-HF trial show that, compared with guideline-directed medical therapy alone, thoracic (T2 to T4) SCS in patients with NYHA functional class III HFrEF, did not lead to changes in LV structural remodeling (LV end-systolic volume index) at 6 months (Figure 6). Moreover, thoracic SCS did not lead to significant improvements in peak Vo2 nor circulating levels of NT-proBNP at 6 months. There were no differences between the groups in freedom from death or hospitalization for HF at 6 months, change on Minnesota Living with Heart Failure Score, change in NYHA functional class or change in 6-min walk distance. SCS appeared to be safe and well tolerated in patients with NYHA functional class III HF, which is consistent with the observation in patients without HF.
In this Lomibuvir study, we were interested in assessing the unique contributions of father education and language input to child language after controlling for the same maternal characteristics. Therefore, we employed a hierarchical modeling approach that allowed us to enter father characteristics as a single final block in our regression analyses, after we considered demographic, child, and maternal contributions. For each regression model, demographic (state of residence, hours/week in childcare, income-to-needs ratio, ethnicity) and child characteristics (distress, birth order) were entered in the first step of the regression to control for mouth potential influences on child language. The second step consisted of maternal variables measuring education, time spent with the picture book and vocabulary when children were 6-months old. The third step consisted of paternal variables, including education, time spent with the picture book and vocabulary when children were 6-months old. Table 3 presents the results of the hierarchical regression analyses predicting child communication skills at 15 months and child expressive language development at 36 months.
Conflict of interest
AcknowledgementsThis research has been supported by the Graduate School, the Faculty of Associated Medical Sciences and the Research Center in Back, Neck, Other Joint Pain and Human Performance (BNOJPH), Khon Kaen University (57211105-5). We thank the director, staff and caregivers of the orphanage and the parents of the home-raised infants in Khon Kaen province. A special thanks is due to all public health volunteers who HO-3867 helped with subject recruitment.
LP, late preterm; NICU, neonatal intensive care unit; ASQ-3, Ages and Stages Questionnaires 3rd edition; CA, corrected age
The objectives of the current study were to compare the risk of developmental delay between LP and term Canadian infants at age 12 months, and to determine infant and maternal factors associated with risk of delay. The research questions were: (1) Compared to term infants, do LP infants have a greater risk of developmental delay as measured by the domains (Communication, Gross Motor, Fine Motor, Problem-Solving, and Personal-Social) on the Ages and Stages Questionnaires 3rd edition (ASQ-3) (35) at age 12 months CA? (2) Controlling for infant and maternal characteristics selected based on the literature, what is dominance hierarchy the association between LP birth status and risk of delay at age 12 months CA?