Several retrospective small studies have indicated that survival

Several retrospective small studies have indicated that survival is incrementally better with larger tumor burden removed with CN; therefore, CN should be mainly used in patients where most of the tumor bulk is in the retroperitoneum or kidney [43–46]. In patients with T4 disease, CN is generally associated with poor survival and should mainly be considered as last resort for palliative purposes in this setting [47]. In patients with non–clear cell histology, the results of retrospective studies are contradictory, with some studies showing worse survival in patients with non–clear histology undergoing CN (compared with patients with clear cell RCC undergoing CN) [48], whereas others showing improved survival in patients with non–clear cell RCC undergoing CN (compared with patients with non–clear cell not undergoing CN) [49].

Sequence of CN in setting of multimodal therapy
With the widespread use of targeted therapy agents in the treatment of mRCC, there has been a significant phenomenon observed in many studies that did not occur with the use of immunotherapy agents, and that is the downsizing of some primary tumors. Many retrospective studies have documented 3X FLAG Peptide in largest diameter primary tumor size between 7% and 24%, with 6% to 23% of responses qualifying as partial response according to the RECIST criteria [50], after the use of various targeted agents such as sunitinib, sorafenib, and bevacizumab [51–54]. However, it is also acknowledged that decrease in tumor size may be owing to increase in necrosis or various responses to widely heterogeneous tumor foci; hence, a reduction in size may not represent the best end point in mRCC. Nevertheless, with this observation, the idea of using targeted therapy as preoperative agents for patients with locally advanced and even mRCC has been considered. In the context of mRCC, the term preoperative or presurgical rather than neoadjuvant should be used to imply that the intent targeted therapy is not curative in this setting, hence, it is not truly neoadjuvant therapy before consolidative surgery.
Although there is no definitive evidence to date that can steer the argument one way or another, the theoretical use of preoperative targeted therapy in the metastatic setting includes downsizing of tumor before CN, which may facilitate surgery for locally advanced tumors with bulky lymphadenopathy or decrease in size of IVC tumor thrombus or both. In addition, preoperative therapy allows for timely delivery of systemic therapy to the metastatic disease and act as a litmus test for better patient selection, such that patients who respond to therapy are most likely to benefit from CN, whereas those that rapidly progress on therapy could avoid potential surgical morbidity and remain on medical treatment without undergoing CN. Several small retrospective series have been published that explore the role of preoperative targeted therapy in mRCC. In a study by Rini et al., 28 patients with unresectable RCC, 19 of which had distant metastases, received continuous daily dosing of sunitinib. A 22% median decrease in primary tumor size, corresponding to a median absolute reduction of 1.2cm, was noted. In total, 13 patients (45%) met the primary end point of being able to undergo nephrectomy after preoperative sunitinib. All patients had viable RCC in the surgical specimen, and surgical morbidity was reported to be consistent with prior experience of nephrectomy in patients without preoperative therapy according to the authors [55]. In another study, Powles et al. [56] examined the outcomes or 66 patients with mRCC who received 2 to 3 cycles of sunitinib before surgery. Sunitinib was administered in 6-week cycles with 4 weeks on and 2 weeks off and was stopped a median of 29 days before CN. Overall, 68% of patients had intermediate-risk disease, and CN was not performed in 12 owing to disease progression. The PFS was 6.3 months (95% CI: 5.1–8.5 months), and OS was 15.2 months (95% CI: 10.3-not applicable), with improved OS for the intermediate-risk group vs. poor-risk group, 26.0 months (95% CI: 13.6-not applicable) vs. 9.0 months (95% CI: 5.8–20.5), respectively (P<0.01). Interestingly, 17 (36%) patients progressed during the 2-week treatment break, although the vast majority stabilized once sunitinib was restarted. This study demonstrated improved survival in the intermediate-risk patients compared to the poor-risk group, although there was no control arm and therefore results should not be generalized. Finally, in a multi-institutional retrospective study by Stroup and colleagues, 17 patients with mRCC underwent upfront CN followed by sunitinib, and 18 underwent preoperative sunitinib therapy followed by planned CN [57]. Of these patients, 11 (61%) had PR or SD per the RECIST criteria and underwent CN, and 7 (39%) progressed and did not undergo CN. Mean times to disease-specific death were 29.2 months for the upfront CN group, 28.7 months for the preoperative sunitinib followed by CN group, and 4.6 months for the preoperative sunitinib group that did not respond and therefore did not undergo CN (P = 0.025). Therefore, it appeared that nonresponders had a poor prognosis, and overall, those with preoperative sunitinib who responded and proceeded to CN appeared to fare significantly better than patients receiving upfront CN and then undergoing sunitinib treatment. Although this is a small retrospective study with a small patient population, it helps to shed light on the dilemma of timing of CN in multimodal treatment of mRCC.

Furthermore we report that a high

Furthermore, we report that a high number of patients (49/113) had at least a GS 7 that is considered as significant disease. In addition, it must be pointed out that 7/112 patients had a high-risk PCa according to the EAU and D׳Amico classifications, thereby associated per se with an increased risk of metastatic spread (www.uroweb.org).
However, one can argue that the definition of “significant PCa” has been discussed in the recent years as some authors define “significant PCa” only from GS 4+3 [16]. If this were the case, in our population only 16 or 12 patients would meet this grade or stage criteria. Moreover, this argument has to be considered when interpreting and comparing different studies on this topic.
In apoptosis inducer
to the work of Pepe et al. [10] where no patient had a biochemical recurrence, in our study 15 patients had a PSA recurrence and 6 patients even died of PCa. Winkler et al. [7] and Kurahashi et al. [13] found more than 20% of patients with biochemical recurrence. Another Asian study reported a biochemical recurrence rate of 8.8% and also Dell׳Atti [17] reported 9% biochemical recurrence rate in a small patient cohort [11].
As expected, most patients with biochemical recurrence had a high GS or adverse pathology (≥pT3a) or had both in the RC specimen. However, 2/15 patients in our patient collective had a GS 5 in the pathology specimens, indicating that also in low-risk PCa PSA measurement should be included in the oncological follow-up analyses. These data are contradictious to Bivalacqua et al. [18] who analyzed the effect of PSA measurement after RC in patients who had a benign prostate pathology. Thereby, the authors of this retrospective study concluded that PSA controls can be avoided in those cases in the routine follow-up. In contrast to these data, we strongly support the opinion that all men with PCa in the RC specimens should undergo regular PSA measurement in the postoperative follow-up visits.
In our patient collective, we found that 40% of patients with a biochemical recurrence after RC died of PCa 9 months to 4 years after surgery. This finding is in strong contrast to Pan et al. [11], Gakis et al. [5], or Winkler et al. [7] who analyzed the mortality rates in patients undergoing RC and found no single PCa-related cause of death.

Conclusion

Acknowledgments

Introduction
Urothelial carcinoma of the bladder (UCB) is the most common urothelial malignancies which accounts for 3.3% of newly diagnosed cancer cases and 2.1% of cancer deaths in the world [1]. Overall, 70% of bladder tumors present as noninvasive urothelial carcinoma, and the remainder present as muscle-invasive disease [2]. So, an accurate biomarker or prognosis factor is essential for efficient management of UCB.
TMEM67, also named Meckelin, is a transmembrane protein encoded by TMEM67/MKS3, localizing to the primary cilium and the plasma membrane [3–5]. Genotype-phenotype analyses indicated that recessive mutations at the TMEM67 locus were associated with dysfunction of primary cilia [4–6]. Primary cilia are ubiquitously present in cell surface organelles with essential functions in cellular proliferation, differentiation and development. Emerging evidences suggest that in many cancers [7–10], primary cilia are markedly decreased or absent. To date, however, abnormalities in TMEM67 and their influence to UCB have not been declared.

Material and methods

Results

Discussion
UCB is genetically heterogeneous [11], with frequent alterations in genes regulating chromatin state, cell cycle, and receptor kinase signaling [12–15] and it is a cancer with high recurrent rate and the 5-year overall survival is still unsatisfactory for advanced disease in spite of the introduction of adjuvant chemotherapy [16]. Current patient prognosis is mainly based on TNM. The high recurrence rate requires close surveillance with cystoscopy that is an invasive test, so an accurate biomarker or prognosis factor is essential for efficient management of UCB.

This study therefore investigated preferred solar exposure of resting

This study therefore investigated preferred solar exposure of resting park visitors on summer and tropical days at various daytimes in the Netherlands through studying visitors’ behavioural response (park attendance, spatio-temporal user patterns) and thermal perception. This way, we obtained evidence-based climate-responsive design guidelines for future park design in moderate climates (Brown and Corry, 2011; Brown et al., 2015). To inform design scientific evidence should be translated into design guidelines in an accessible and understandable way (Prominski, 2017) so that design professionals are encouraged to take microclimate aspects into account when shaping outdoor spaces (Nassauer and Opdam, 2008; Ward Thompson, 2013).
Consequently, the main research question was: What are evidence-based design guidelines for thermally comfortable future parks in moderate climates? To answer this main question, the following sub-questions were formulated:

Methods and materials
A combination of quantitative and qualitative methods delivered an empirical database to inform design guidelines for future parks. By combining surveys, unobtrusive observations and spatial analysis we related park visitors’ behaviour and thermal perception to meteorological reference data and spatial characteristics of the parks. The conceptual framework of this study is shown in Fig. 1.

Results and discussion

Conlusions: design guidelines for future parks
Investigations on human behaviour of resting park visitors on summer and tropical days (Ta max>25°C and>30°C, respectively) clearly indicate the need for creating a variety of solar exposure conditions when designing parks of the future. Regarding research question 1 (What is the importance of microclimate on the spatial preferences of resting park visitors?), survey results emphasize the central role of microclimate, in particular solar exposure, for park visitors when choosing resting locations. The survey results regarding research question 2 (What is the thermal perception of resting park visitors on summer and tropical days?) showed that park visitors described their perception of thermal comfort at their actual resting locations on a high level during both, ‘summer’ and ‘tropical’ days. Thus, even though park visitors experienced a heat wave, they abacavir sulfate were able to find resting locations in the parks that they perceived as thermally comfortable. Observational results related to research question 3 (How does extreme air temperature in summer influence daily park attendance) indicate that daily park attendance significantly decreases with rising air temperature (Tamax). In contrast to earlier studies, our results suggest that park attendance decreases with rising temperatures in moderate climates. This outcome once more demonstrates the need for climate-responsive park design, encouraging outdoor recreation and activity during warmer future climate conditions (Brown et al., 2015). The results concerning research question 4 (What are the user patterns related to solar exposure of resting park visitors on summer and tropical days?) indicate that air temperature (Ta) governs solar exposure preferences of park visitors. With increased Ta the number of park visitors increased significantly in the shade and decreased in the sun. A tipping point at 26°C was found beyond which visitors prefer the shade to the sun.
Observational results, moreover, show that solar exposure preference of resting park visitors is nuanced; not only sun or shade but also half shade spaces are used to find thermally comfortable places under various thermal conditions (summer and tropical) and on various times of the day (from 11:00 to 17:00). Based on the observational data we derived a typical ratio of resting park visitors in sun 40%, shade 40% and half shade 20%. Pertaining to research question 5 (What are spatial typologies for optimal park use on summer and tropical days?) this study provides a typology of vegetation configurations, that are spatially explicit and communicated as visual information (icons) to guide future park design (Brown and Corry, 2011; Prominski, 2017). Accordingly, designers should create broad varieties of microclimates, from open lawns and sunny spots around single trees or groups of trees (which are preferred on summer days), to shaded areas provided by solitary trees, small groups of trees, edges of tree clumps, boscages and scattered trees (preferred on tropical days). In order to create such broad ranges of microclimates in parks designers need to systematically analyse solar exposure patterns and consider diurnal and seasonal shapes and sizes of shade provided by different tree species. Shade analyses in GIS applications (as applied in this study) or in 3D modelling software are useful tools for professional designers to analyse existing and new park shade patterns.

Table shows the correlation coefficients of the eight health

Table 4 shows the correlation coefficients of the eight health-related and other GBH elements in a matrix form. All the coefficients are statistically significant (p≤0.01), thereby indicating that there is at least a certain degree of relationship between the health-related and the other elements. The strongest three coefficients in each group of health-related elements are highlighted in bold.
The presence of the interrelations is determined by the magnitude of the correlation coefficients which range from weak (r=0.1–0.3), moderate (r=0.4–0.6) to strong (r=0.7–0.9) (Dancey and Reidy, 2011). By counting the number of each level of correlation, it is observed that all the coefficients demonstrate either a weak or a moderate (underlined in Table 4) correlation. Specifically, the two park quality-related dimensions, “overall quality of parks and green spaces” and “quality of facilities of parks and green spaces”, have a relatively stronger interrelation with the other non-health-related elements because 13 and ten of out 15 coefficients display a moderate level of correlation, respectively.
The results of the multiple regression analysis testing models of green brand elements are presented in Table 5. In these models, multicollinaearity is discounted for the analysis because all the variance inflation factors are below three, the critical value (Fox, 1997). Each of the eight health-related factors denoting the health components in the green brand are used as the single dependent variable separately. The other health or non-health-related elements are independent variables. The analysis of a particular health-related 17-aag included all of the other elements in the model because this maintains the integrity of a green brand. There is no ground of assumption in theory to exclude the health-related elements from the model, but the results may confirm whether these health-related elements are significant determinants in the green brand which emphasizes the other health factors. The result shows an acceptable overall fit of the models, with adjusted R-Squares ranged between 0.384 and 0.637. The models are reliable because the F-values are statistically significant (p≤0.01), whereas half of the models reach an R-Square value of about 0.6.

Discussion
The eight regression models demonstrate the underlying factors which determine the eight health-related GBH elements. Although the models have a relatively low explanatory power in predicting the influential green brand attributes against the health dimension, all the extracted elements in the models are statistically significant for drawing important conclusions about the relationships and directions between the green brand attributes which affect the health dimension of the brand (Abelson, 1995).
The values of the standardized coefficients in each model show the most significant determinants of each health-related element. It is noticeable that the key determinants of each health-related element are the other health attributes (highlighted in italics). The “pleasant experience in parks” (Model 1) is mainly determined by the perception of trees and greenery beauty (β=0.462). The “trees and greenery beauty in the city” (Model 2) is strongly determined by the perception of “landscape and hillside beauty” (β=0.438) and “pleasant experience in parks” (β=0.304). The perception of “landscape and hillside beauty” in the city (Model 3) is largely influenced by “trees and greenery beauty in the city” (β=0.529). The “recreational opportunities in parks” perceived by the respondents (Model 4) is affected by “landscape and hillside beauty” (β=0.283). The “overall quality of parks and green spaces” (Model 5) is highly determined by the health-related factors, namely, the quality of park facilities, trees and 17-aag greenery beauty and park safety (sum of β=0.829). The “quality of facilities of parks and green spaces” (Model 6) is mainly influenced by overall park quality, accessibility and safety (sum of β=0.676). The “accessibility to green spaces” (Model 7) is associated with quality of park facilities and park safety (sum of β=0.398). Lastly, “safety in parks and green spaces” (Model 8) is also determined by overall park quality, accessibility and quality of park facilities (sum of β=0.564). A significant and relatively large value of a constant and relatively lower adjusted R-Squares in this model reveals the existence of more external factors affecting the independence of recreational sites and activities in Hong Kong. These external factors may include a strong top-down urban greening policy, which causes the local residents to indulge far less in public participation and thus is probably a weaker association between health-related and other attributes in a green city brand. Its interrelation with the landscape and hillside beauty can be explained by the presence of a large coverage of country parks that are mostly located in the mountainous areas of the territory.

Interestingly one female patient whose diagnosis could not be ruled

Interestingly, one female patient whose diagnosis could not be ruled out as malignant disease by many methods, including EUS, was finally diagnosed with inflammatory pseudo-tumor after explorative laparotomy. This case exemplifies the difficulty in clinically distinguishing malignant from benign disease. A case of immunoglobulin G-related pseudo-tumor in the rora mimicking pancreatic cancer was reported by Kim et al. (Park et al. 2008). We think this case may be an example of immunoglobulin G-related pseudo-tumor involving the stomach, which is undistinguishable from benign and malignant diseases. Thus, there are subgroups that are undistinguishable from benign and malignant diseases on EUS. Further studies of these subgroups are needed, and additional workup is needed to avoid unnecessary laparotomy.
Our study has some potential limitations. First, we could not use standard EUS protocols because our study was retrospective. Second, although our study contained more diverse disease categories compared with previous studies, we could not include all diseases in which there are large gastric folds. However, this is difficult limitation to overcome because patients with large gastric folds are relatively rare. Third, we included patients without definite histologic diagnoses and used clinical follow-up examinations to make our diagnoses; however, previous studies have also used this method (Gines et al. 2006).

Conclusions

Acknowledgments

Introduction
Tumor angiogenesis, required for invasive tumor growth and metastasis, is an important point in the control of cancer progression (Folkman 2002; Stacker and Achen 2013). Ischemic tumors rarely grow larger than 3 mm3, but once they become vascularized, their growth rate may significantly accelerate (Folkman and Shing 1992). Microvessel density (MVD) has been the most common index of tumor vasculature since 1972 (Brem et al. 1972). Several reports suggest that higher tumor MVD correlates with tumor aggressiveness rora and poor survival in several malignancies, including liver, breast, gastric and pancreatic tumors and neuroblastoma (Couvelard et al. 2005; Fernandez-Aguilar et al. 2006; Poon et al. 2002; Ribatti and Ponzoni 2005; Zhao et al. 2005). Interestingly, studies have failed to demonstrate any significant correlation between MVD and tumor progression or patient prognosis (Hillen et al. 2006; Marioni et al. 2005; Qian et al. 2009). Such a discrepancy could be explained by the technical drawbacks in the evaluation of MVD. The diversity of tumor vasculature could also be a contributor.
Hepatocellular carcinoma (HCC) is a common malignancy with poor prognosis in China and other developing countries (Wei et al. 2014). The vasculature of HCC is suitable for morphologic classification (Chen et al. 2011; Ding et al. 2011). HCC vasculature can be classified into two major types of vessels based on morphology: (i) capillary-like microvessels, which possess a complete basement membrane and are surrounded by pericytes, and (ii) sinusoid-like vessels, which have a long, wide lumen structure and insufficient pericytes (Chen et al. 2011; Kin et al. 1994; Tanigawa et al. 1997; Yamamoto et al. 2001). Recent studies have also reported that HCC patients with sinusoid-like vasculature have a shorter survival time, although the intra-tumor MVD of a tumor with sinusoid-like vasculature is significantly less than that of a tumor with capillary-like microvessels (Chen et al. 2011; Ding et al. 2011). However, there is currently no non-invasive method for the evaluation of HCC microvasculature.
The ability to visualize angiogenesis through non-invasive methods may provide new opportunities to stratify patients for anti-angiogenic treatment and monitor treatment efficacy (Iagaru and Gambhir 2013). Contrast-enhanced ultrasonography (CEUS) of the tumor vasculature in animal models appears to be effective in evaluating tumor vasculature in a non-invasive manner (Forsberg et al. 2011; Zhou et al. 2011; Zhuo et al. 2014). CEUS has been reported to have an effect on the evaluation of microvascular morphology and angiogenesis in HCC (Hatanaka et al. 2010; Schacherer et al. 2010; Xiao et al. 2010; Zheng et al. 2013). The purpose of this study was to identify the parameters of pre-surgical contrast-enhanced ultrasonography for the classification of HCC, based primarily on the different tumor vasculature morphologies related to the prediction of post-surgical patient prognosis.

In the experiments the spectrum of the coherent

In the experiments, the spectrum of the coherent polariton emission was monitored as function of the time delay t0 between the white light excitation pulse and the strain pulse arrival time to the QW. The latter is defined as shown in Fig. 1(e). The results are shown in Fig. 2 for the UP [panel (a)] and LP [panels (b) and (c)]. Clearly, the polariton spectrum, which under stationary conditions consists of the well-defined UP and LP resonances (Fig. 1(b)), undergoes enormous changes when the strain pulse is hitting the QW. THz modulation of the UP alzheimer\’s disease (Fig. 2(a)) by several meV occurs. Regardless of the smaller LP modulation amplitude (Fig. 2, panels (b) and (c)), for certain values of delay t0 the LP spectra show a remarkable, well defined structure with spectral fringes at the flanks of the main resonance. The most pronounced sidebands with up to 3 fringes are observed for high amplitude strain pulses (Fig. 2(b)) in the delay intervals t0=10–25ps and t0=90–105ps, which correspond to the linear parts of the strain evolution. Fig. 2(d) shows the reflectivity spectrum R(t0, E) for a delay t0=17ps, at which several fringes are clearly detected.
We associate the experimentally observed spectral sidebands with the specifics of the nonadiabatic THz optical frequency modulation. To illustrate that this observation is a general phenomenon, we consider a scalar harmonic oscillator decaying with time-dependent frequency ω(t) and decay time . We demonstrate that the oscillator spectrum shows a series of sidebands in the case when ω(t) is changing linearly with time and the frequency shift within exceeds the stationary spectral width. A case-specific numerical analysis, where the temporal evolution ω(t) is taken to be identical to the experiments, shows good agreement with the experimental results [16].

Destruction and recurrence of excitons by acoustic shock waves on picosecond time scales
The same sample and experimental technique as described in Section 2 and shown in Fig. 1 was also used in the next experiment. The main difference concerns the detuning value ΔE0=− in the absence of the strain pulses. In the present experiment the part of the wafer was chosen where ΔE0=0, which corresponds to the strongest mixing of the pure exciton and photon resonances resulting in the vacuum Rabi splitting 4meV as can be seen from Fig. 1(f).
Fig. 3 shows contour plots of the reflectivity as function of time delay and photon energy for four different pump fluences on the metal film. Time zero corresponds to the moment when at low pump fluence (2.5mJ/cm2) the maximum compressive strain hits the quantum well, and the dotted lines mark the times at which changes by the strain can be resolved. Beforehand, in all cases the two polariton modes with 4meV Rabi splitting are seen.
At the lowest pump fluence (Fig. 3(a)) the induced modulations occur rather slowly, so that the evolution of the two polariton resonances with time can be followed well in the spectra. The polariton mode energies undergo a smooth oscillation with increasing delay, following the compressive and tensile parts of the acoustic wave packet. This smooth behavior reflects a continuous change of the exciton–photon mixing in the polariton states by the strain pulse modulating mostly the exciton energy, while the impact on the resonator is negligible due to the smallness of changes in cavity length and elasto-optical constant by the strain [24]. Note that in the delay range up to a few 10ps sidebands (see Section 2) appear on the low energy side of both polaritons, relative to which they shift in parallel with time. These sidebands become more pronounced with the increase of the excitation density to 6.25 and further to 10mJ/cm2 (Fig. 3(b and c)). Therefore, the resonances lose their spectral sharpness because of the modulation induced chirping of the optical transitions, as described before and in Ref. [15]. Still the resonance centers can be followed well in time, from which the polariton energies are seen to change smoothly. In particular, the observation of two polaritons for all delays underlines that the exciton state is preserved and strong coupling is maintained.

Experimental validation The ultrasound device including ultrasound generator and output

Experimental validation
The ultrasound device (including ultrasound generator and output terminal), whose frequency was 20kHz and power was adjustable in the range of 0–600W, is shown in Fig. 7. The vibration of the ultrasound generator was amplified through the transducer to generate ultrasound, finally ultrasound was introduced into the medium through the booster. In this experiment, ultrasound was introduced into water in a glass container with size Φ 100mm×200mm, the booster was immersed in water 10mm deep, the power of ultrasound generator was 200W. The diameter of the booster was 30mm, the water level in the container was 180mm. A high-speed CCD snapping system was utilized to record the fluid flow. Numbers of observing points in the flow field were selected to calculate the displacements of bubbles by a series of recorded frames, as a result, the velocity betaxolol of each bubble were determined to reveal the appearance of streamline in the flow field. The flow field recorded by the high-speed CCD system is shown in Fig. 8, from which it can be seen that there was intense turbulence along the center-line below the booster’s tip.
As the flow field was symmetric, 34 typical points roughly uniformly distributed in the right side were selected as the observing points, as illustrated in Fig. 9(b). Each observing point has a start and an end location, the former location stands for the position where the observing point lies in the first frame of video recording, and the latter one was the location of the observing point in the last frame of video recording. The velocity vector of each observing point was obtained through the calculation based on its start and end positions and the time differences between two consecutive recorded frames, the results are listed in the table below. The streamline of the whole flow field is plot in Fig. 9(b).
The velocity distribution in water obtained by numerical simulation is illustrated in Fig. 2(a), from which it can be seen that velocity in the area where y<20mm is the highest, it is helpful to compare the experiment and simulation results in this area. The points along the depth direction (x direction) at the locations where y=0, 15mm and 20mm were selected for study, the velocity at these points was measured using high-speed CCD system, the comparison of velocity in experiment and simulation is shown in Fig. 10. The velocity in experiment is approximate to that in simulation, but the experiment results are slightly higher than the simulation results, as the ultrasonic energy released during experiment increased the water temperature, leading to the decrease of water’s viscosity. When the water temperature increased from 0°C to 40°C, the viscosity decreased from 1.7921×10−3Pas to 0.6560×10−3Pas [31], as a result, the velocity of water flow increased. However, the heating effect of ultrasonic treatment is ignored in simulation, the viscosity of water is considered to be a constant, in this way, the velocity in experiment is higher than that in simulation. The variation trends of velocity in experiment and simulation are similar, indicating that numerical simulation reveals the ultrasonic streaming correctly.
The comparison of the streamline obtained in experiment and simulation is illustrated in Fig. 9, it can be seen that the simulated streamline is in agreement with the experimental one.

Conclusions

Acknowledgement
This research was supported by National Natural Science Foundation of China (No. 51075299).

Introduction
Despite the many and varied potential applications of high power ultrasound technologies for different treatment purposes, industrial scalability of ultrasonic treatment processes is still difficult to achieve. One of the crucial elements of ultrasound scalability is the quantification of energy losses involved in the conversion of the electrical energy into several forms of mechanical energy [1]. The ultrasonic energy distribution of acoustic cavitation effects within an ultrasonic reactor is also important for scalability as this aspect allows engineers to determine the optimum operating conditions for a particular application. Furthermore, scrutinizing energy conversion in ultrasonic reactors enables researchers to rigorously compare results of different experiments and report reproducible reaction conditions [2].

Acoustic waves at any frequency first couples into the

Acoustic waves at any frequency first couples into the corresponding surface mode of the lower surface, Fig. 3. 22a delay of the onset of the upper PnC ensures that component of the incident wave reflected off the lower PnC at an angle θ with the horizontal axis cannot couple the upper PnC surface mode, while it is reflected back into air by the vertical surface of the upper PnC. Thus, any wave component propagating along the upper PnC surface can only be excited by coupling from the lower surface so that the wave initially propagating along the lower surface starts coupling into the upper surface, and then back into the lower surface, Fig. 3.
For a better understanding of mode coupling, acoustic pressure field is probed on the horizontal dashed lines marked as and in Fig. 3(a), which are a/5 away from the respective surfaces. The plots below the FEM simulation results in Fig. 3 present variation of and along the surfaces, which are normalized to a common value in each plot for simplicity. These plots reveal that the peak of appears at higher x as f increases, implying that increases with f, as expected. is visually calculated from the variations of and in Figs. 3 and 4 as the distance between the first minimum of the envelope of (where acoustic atm inhibitor is maximally transferred to the upper surface) and the following maximum (where the energy is maximally coupled back into the lower surface). Visually calculated values in Fig. 3 are 36.3, 38.4, and 42.3 at 1.500MHz, 1.520MHz and 1.540MHz, respectively. Although they follow the general trend of increasing with f, these values are somewhat different from the above-mentioned values calculated from the BS.
The plots of and in Fig. 3 show that the dash-dotted envelope curves do not follow a smooth variation. Instead, each envelope demonstrates a fluctuation, apart from the variation reflecting coupling. The fluctuations are due to the beating behavior of the surface modes on single surfaces [25,27]. The beating occurs due to the fact that each mode at a specific is associated with a counter-propagating mode displaced by a reciprocal lattice vector corresponding to surface periodicity [25]. As the beating and mode coupling superpose, it is difficult to tell where the minima and maxima of the envelope curves occur. Thus, is loosely calculated from Fig. 3 by measuring the distance between a minimum and subsequent maximum of within the coupling region.
The acoustic wave leaves the interacting PnCs mainly from the upper surface at f=1.500MHz, as the device length is such that almost a complete cycle of coupling back and forth is achieved and a new cycle begins, Fig. 3(a). As the frequency reaches 1.520MHz, wave output from the lower PnC is more dominant, Fig. 3(b). Finally, the wave leaves the device almost totally from the lower PnC at 1.540MHz, Fig. 3(c). If one probes the acoustic output from each surface and compares them, variation of coupling length with frequency can be calculated.
FEM simulation results for W=3.5a corresponding to the frequency range where drops with f is presented in Fig. 4 at frequencies of 1.565MHz, 1.570MHz and 1.575MHz. The corresponding values calculated from BS are 47.45, 46.53 and 43.99, respectively. In contrast, measurement of distances in Fig. 4 reveals =42.0, 41.6 and 38.4, respectively. These values are calculated by again measuring the distance between a minimum and the subsequent maximum of the envelope curve for . They are considerably smaller than the expected values. The reason is again the beating behavior that interferes with mode coupling. Thus, it is difficult to tell where maxima and minima occur.
Inspection of Fig. 4(a) shows that there is comparable wave output from the lower and upper surfaces at 1.565MHz. In contrast, waves leave the system mainly from the lower PnC at 1.570MHz and 1.575MHz, Fig. 4(b) and (c). Although a general conclusion cannot be drawn by inspecting Fig. 4 only, it is evident that the ratio of output acoustic power from the two surfaces vary rapidly with frequency. This will be clarified later in the discussion of Fig. 7.

The parameters and appearing in Eq are given by The

The parameters and appearing in Eq. (7) are given by:
The potential functions corresponding to the scattered waves are expressed as:where stands for the Hankel function of the first kind of order n, and , and are unknown coefficients. Considering the discussed potential functions for the scattered and incident waves in the matrix, the displacement field is given by:
Now, applying the continuity condition for stress and displacement at the cylinder/matrix interface, the unknown coefficients are identified. Continuity condition for stress and displacement are:
To study the scattered waves, the form function is considered. For the case of an incident everolimus wave, is obtained as:and for an incident shear wave, it is:
In the case of scattered compression waves, is equal to and in the cases of scattered SH and SV waves, it is equal to and , respectively.
In this paper, for the purpose of analysis of multiple scattering, an infinite plane wave of frequency incident on a grating of N infinitely long transversely isotropic cylinders, with outer radius aligned in one row and embedded in an isotropic matrix is considered. The wave vector makes an angle with respect to any of the cylinder axes. Corresponding to each cylinder, a local cylindrical coordinate system is considered where each local z-axis coincides with the cylinder axis while the local x-axes (corresponding to ) are along the incident wave direction. To properly account for multiple scattering, by employing the Graf’s Addition Theorem, the scattered wave from any cylinder is considered as an incident wave for the other cylinders. Therefore, considering the type of the incident wave, the incident potential functions take a more general form as follows:
The parameters , and for the case in which the incident wave is scattered from the cylinder-number c to cylinder number j (for ) are calculated as [18]:and for , we get:
Now, with the aid of Eqs. (17) and (18), together with the equations presented for the scattering from a single cylinder, analysis of multiple scattering is possible.
To take into account the viscoelastic behavior of the matrix material, the Havreliak–Negami model is employed. Use of this model yields complex Lame constants which are functions of the frequency. In this regard, the frequency dependence of the complex shear modulus is expressed as [16]:where (relaxed modulus) and (unrelaxed modulus) are the limiting values of the shear modulus at low and high frequencies , respectively is the relaxation time and are dimensionless material parameters. is the loss factor expressed as:where and:
Therefore, is dependent on the ratio of to . Adopting the hypothesis of a real Poisson ratio, the Lame constants are given as [16]:

Experiments
In order to validate the numerical results of the analytical model, a number of experiments are conducted. These experiments are performed by using the short-pulse Method of Isolation and Identification of Resonances (MIIR). In this method, a broad-band short-pulse is incident on the target by an ultrasonic transmitter probe. The interaction of the incident wave with the cylinder results in a backscattered field that is picked up by the same ultrasonic probe which acts as both transmitter and receiver. The schematic of the experimental setup everolimus is illustrated in Fig. 3.
In the measured signal, the first echo is the specular echo and the echoes succeeding it are due to resonances of the system. The frequency spectrum of the backscattered signal comprises of the effects of the waves scattered from the cylinder and the frequency characteristics of the transducer. After filtering the frequency characteristics of the transducer, the frequency spectrum of the remaining signal would represent the form function of the cylinder versus the dimensionless frequency ka. The range of variations of ka for each experiment depends on the probe bandwidth, the cylinder radius and the mechanical properties of both cylinders and surrounding media. Therefore, in order to make changes to the frequency range, either the cylinder radius or the probe bandwidth should be changed.

Alternatively when the response of a given spatial

Alternatively, when the response of a given spatial-frequency is of interest as a function of defocus, it is convenient to express this OTF after only transforming the lateral dimension to Fourier-space. The resulting OTF has reciprocal-space lateral units (those of spatial frequency) but retains a real-space unit in the beam direction (equivalent to defocus or equally z-height). Once such a 3D OTF is calculated it can be sectioned parallel to the beam direction (vertically in Fig. 4) for any given spatial frequency to yield the transfer function corresponding to sample features with the corresponding lateral spacing. We extract a depth resolution of 9nm for the 0.28nm minimum transverse spacing of the Zr lattice, only a couple of nanometers more than the 7nm depth of field [10]. For the larger 0.39nm Ti-Ti and Sr-Sr spacings we calculate the depth resolution to be 11nm. Therefore EELS spectrum images acquired with sufficient transverse resolution to resolve these spacings also posses significant depth resolution.
Atomic resolution EELS spectrum images were acquired from regions appearing to contain YSZ buried beneath STO from HAADF imaging. By using the high tension fine defocus control of the UltraSTEM 100 we were able to obtain pairs of spectrum images taken in quick succession from the same area of the sample but with the probe focused to different depths. The Zr maps extracted from one such pair of spectrum images are displayed alongside the simultaneously acquired HAADF and MAADF images in Fig. 5. The Ti and Sr maps from the same slices are shown in Fig. 6, alongside composite images of the Zr, Sr and Ti signals combined together as the red, green and blue leukotriene receptor agonist respectively. The optical slices were taken with the probe focused to the entrance surface and 18nm into the depth of the film.
Each slice consisted of 35 by 146 EELS pixels with 0.05s exposures. Subpixel scanning was performed in a 32 by 32 grid inside each EELS pixel to provide superior resolution in the simultaneously acquired HAADF and MAADF images. The principle component analysis method of [32] was used to eliminate noise in the atomic-resolution EELS elemental maps as described in [33]. For the Ti maps we again used the L-edge, however when extracting the Sr and Zr elemental maps for the optical sectioning we utilised the Sr and Zr M-edges rather than their L-edges due to the proximity of the M-edges to the Ti L-edge, which was needed to record all the edges at once on the smaller CCD of the Enfina spectrometer, and also because of their higher cross sections. The Ti L-edge fine structure was used to fine tune the calibration of the energy scale. Although the Sr and Zr M-edges are extended and overlap, they are offset in energy and have fine structure features appearing at different energies. The Zr M-edge has a pair of peaks appearing between 330 and 355eV where the Sr M-edge has no fine structure and only a decaying tail, and the Sr M-edge has a pair of peaks between 270 and 286eV where the Zr edge is relatively flat. For the Zr edge, background subtraction fitting was performed in the flat region just after the pair of peaks at the Sr M-edge maximum. For the Sr edge the background fitting was performed between 218 and 240eV, which balances the falloff of one peak in the Zr edge with the rise of the broad peak appearing just before the Sr integration window.
Clear differences are seen between the two spectroscopic optical slices. In the slice taken at the entrance surface of the sample (0nm defocus), the HAADF image shows the alternating pattern of bright and dark columns associated with Sr and Ti columns in STO from top to bottom, and the Zr map reveals the presence of a Zr containing region but without any lattice contrast. However in the slice taken with the probe focused 18nm further into the depth of the sample (−18nm defocus) in the same area, a region of YSZ like contrast appears in the upper portion of the HAADF image, with all neighbouring columns having similar intensity. Here the Zr signal also sharpens into a lattice with precisely the periodicity expected for YSZ (compare to the overlaid Zr lattice model in Fig. 5). This demonstrates spectroscopic depth sensitivity with EELS. The Zr map at zero defocus is an out of focus version of the lattice seen at −18nm defocus. We note that this lattice cannot simply be an artefact of the PCA treatment rather than depth sensitivity as if this were the case the lattice would also appear at zero defocus.