Figs and To investigate the photocatalytic activity of

(Figs. 7 and 8)
To investigate the photocatalytic activity of nano-sized CP 1 under UV light irradiation, we selected methylene blue (MB) as the model dye contaminant due to the chemical stability and poor biodegradation. The detailed photocatalytic experiment procedures are depicted in ESI. The degradation of MB was monitored by the characteristic UMI-77 cost at approximately 664nm. As shown in Fig. 9, the absorption peak of MB significantly reduced along with the reaction time. In addition, the control experiment was studied under the uniform conditions without any photocatalyst. Fig. S6 illustrates that no noteworthy decrease of the characteristic absorption was found in the control experiment. The changes in the C/C0 plot of the MB solution against irradiation time are depicted in Fig. 10 (wherein C0 is the initial concentration of the MB solution and C is the concentration of the MB at any given time t). It can be seen that the photocatalytic efficiency reached approximately 90.2% in the presence of nano-sized CP 1 after 120min under UV light irradiation. However, only 11.9% of MB were decomposed without any catalyst. The increased photocatalytic degradation efficiency indicates that nano-sized CP 1 is an excellent candidate as photocatalysts in decomposing MB under UV light irradiation. Furthermore, when nano-sized CP 1 was placed into an aqueous solution of the MB in a dark environment for half an hour, there is no obvious decrease in the absorbance value, which may avoid the possibility of adsorbing such a dye molecule into the frameworks.
In order to study the reproducible ability of nano-sized CP 1, the repeated photocatalytic experiment was also performed. The photocatalytic efficiency of nano-sized CP 1 in the repeated experiment did not significantly change after three cycles, indicating that the crystal materials were stable and reproducible for the degradation of MB (Fig. 11). The XRD patterns of nano-sized CP 1 were almost identical to those of the original CPs after the reactions (Fig. S2).
To detect the possible photocatalytic reaction mechanism of nano-sized CP 1, isopropanol, benzoquinone and ammonium oxalate were added into the photocatalytic experiment as the scavenger for OH, O2− and (h+) radicals, respectively [53,54]. Fig. 12 illustrates that no obvious decrease of the photocatalytic efficiency was observed in the presence of benzoquinone or ammonium oxalate, proving that O2− and (h+) radicals are not the main reactive species. However, isopropanol can greatly suppress the photodegradation of MB solution, which suggests that the photodegradation process of MB is mainly caused by OH radicals. The possible photocatalytic reaction mechanism for the above degradation reactions is proposed as follows (Scheme S1). Under the high-pressure mercury lamp irradiation, the electrons (e−) of nano-sized CP 1 could be excited from the valence band (VB) to the conduction band (CB), resulting in the equal amount of positive vacancies left in the VB (holes, h+). Then the electrons combined with O2 absorbed on the surface of photocatalysts to produce oxygen radicals (O2), which will transform into hydroxyl redicals (OH). At the same time, the hydroxyl (OH−) absorbed on the surface of photocatalysts reacts with the holes (h+) to yield hydroxyl radicals (OH). Finally, hydroxyl radicals (OH) can effectively degradate the MB.

A new nano-sized Co(II) coordination polymer, [Co(Hbibp)(nbta)] (1), was synthesized by sonochemical irradiation. The crystal structure of CP 1 consists of a 1D chain with the SP 1-periodic net (4,4)(0,2) topology, then the chain can further expand into a 2D supramolecular sheet with the SP 2-periodic net (6,3)Ia structure by the N−H⋯O hydrogen bond interactions. Effects of the sonication time and ultrasonic power on the morphology and size of nanoparticles were also studied. The results demonstrate that the size of nanoparticles increased with the increasing sonication time and the higher ultrasonic power led to the decrease in nanoparticles size. Moreover, nano-sized CP 1 can be considered as heterogeneous photocatalysts for the degradation of methylene blue (MB) under UV light irradiation.

The aim of this paper is

The aim of this paper is to investigate whether the thickness of steel plates can be estimated from ultrasound transmission measurements in air. The main challenge of these measurements is the low signal-to-noise ratio in the signal transmitted through the steel plate. Steel has a high acoustic impedance, around 46 Mrayl, which yields a large transmission loss from air to steel, approximately 87dB. This limits the amount of 69 8 cost that is transmitted into the steel.
When the incoming acoustic field deviates from a plane wave, the relation between plate thickness and resonance peaks is more complicated, involving shear wave conversion and the angular distribution of the incoming sound field. Good theoretical models for the effect of finite sound field reflected from or transmitted through elastic plates have been described in the literature [24]. Such models provide more accurate, but also more complex, descriptions of the transmission coefficient of the fluid–solid–fluid system.



We have demonstrated a method to measure the thickness of steel plates in air, using air-coupled ultrasound with through transmission. The method can distinguish between absolute difference in thickness of 0.15mm and 1.5% relative.
A theoretical model has been applied using the angular spectrum method. The theoretical spectra was found to predict the frequencies for and modes to within 1% of the measured values. The frequency of the mode was observed to be shifted down.

Process optimization of mineral processing requires a rigorous mathematical and economic-mathematical methods for calculating the optimal separation limits of physical properties variation range of the feedstock particles [1].
Various methods and devices of ultrasonic testing, which found application in process automation in [2–14] are discussed. It is noted the advantages of these methods, such as high accuracy and reliability in aggressive media parameters measuring. Thus, the use of these methods is one of the most promising approaches in the development of measurement systems for process automation.
The known ultrasonic testing methods of the pulp parameters allow to identify two of its main characteristics – density and particle size distribution [15]. The volume ultrasonic vibrations are generally used for the parameters measurement.

Materials and methods
The theoretical analysis results of the volume ultrasonic vibrations propagation in the gas containing suspensions is presented in [3,4].
The main characteristic of the ultrasonic radiation field is determined from the kinetic equation. Here is the intensity of the ultrasonic wave (with wavelength ), which is defined as the radiation power passing through a unit area perpendicular to the direction of the point per solid angle unit. – is the unit vector defining the direction in space, is the radius vector defining the position of a given point in space.
Kinetic equation which is solved by function obtained from the energy balance in the elementary volume of the phase spacewhere and are the total cross sections of the ultrasonic wave absorption and scattering on the particle;n – particle concentration (number of particles per volume unit), is the corners differential energy scattering cross section on the solid phase particle, – the density function of the ultrasound radiation source, which determines the average amount of energy emitted from the phase volume unit per unit of time.
Under the phase coordinates means a series of variables , and and the elementary phase volume is determined by the product .
The meaning of this equation is as follows: change in the intensity of the ultrasonic beam, which has a direction at a point is occurs, firstly, due to its absorption and scattering (the first term of the right side), secondly, due to scattering of energy flow, which previously had the direction in the direction (the second term of the right side), and, finally, due to the energy coming to this beam from the sources (the last term of the right). Eq. (1) can be reduced to an integral equationwhere ; is the Dirac delta function; – free term of the integral Eq. (2), which determines the intensity of the unscattered ultrasonic wave .

purchase NSC59984 Ultrasound elastography UE and contrast

Ultrasound elastography (UE) and contrast-enhanced ultrasound (CEUS) are two latest developments in ultrasonography of carotid plaque, measuring plaque elasticity and neovascularization, respectively [3,16–18]. To date, there is no research comparing or combining these two techniques for assessment of carotid plaque. The studies involving both UE and CEUS are focused on diseases of other tissues or organs, such as liver tumors [19], prostate tumors [20], testicular infarction and tumors [12,21], and thyroid nodules [22]. However, the two ultrasonic modalities are not performed simultaneously, and they are often conducted with two different probes or even used with two different devices. Thus, the image slices for UE and CEUS are not aligned either spatially or temporally, resulting in variability of measurement when comparing elasticity and neovascularization. Furthermore, the elastography adopted in these studies is usually the free-hand purchase NSC59984 elastography using axial palpation on tissue with the transducer to generate strains [23–25]. This palpation-based strain elastography is not suitable for strain measurement of carotid plaque, because the strains in plaque can be spontaneously generated by internal vascular pulsations due to the cardiac motion and pulsatile blood pressure [24,26]. Therefore, it is highly desired to develop an elastographic modality that depicts the strains within plaque caused by natural vascular pulsations.
There are several elastography methods recently presented for detecting the aforesaid naturally induced strains with ultrasound (US) speckle tracking applied on either radiofrequency (RF) [3,5,7,11,27] or standard B-mode data [27–29]. However, in a context of investigating relation between IPN and plaque elasticity, CEUS is one required imaging modality for depicting IPN, and acquisition of extra data (RF or B-mode) besides CEUS for elasticity visualization will demand new hardware or increase complexity of data acquisition procedures. Till now, RF data are not available for most commercial ultrasound imaging equipments. In addition, dual modality acquisition of both CEUS and B-mode may also decrease frame rate for each modality and reduce signal-to-noise ratio for B-mode due to low mechanical index used for CEUS, which is disadvantageous for following image analysis.

Materials and methods


It is revealed in our study that the plaques with more IPN are softer. It is in agreement with the study by McCormick et al. [42], who detected high strains in the plaque–adventitia interface of a plaque where the neovascularization originated. In that pioneering study, only one plaque with potential IPN was used for illustrative purposes. Here we have extended the population to a clinical dataset of 38 plaques and have employed CEUS for direct visualization of IPN. Furthermore, our study has demonstrated that the plaques with more IPN tend to be more elastically heterogeneous. Given our findings, it could be speculated that the neovessel itself is softer compared with other compositions within a plaque, or that the neovessel could stimulate or assist some other plaque components that are responsible for elevated plaque elasticity. The underling mechanism of the association between plaque elasticity and the IPN needs to be elucidated; however, it is beyond the scope of this study.
CEUS image has lower spatial resolution compared to RF data, and it exhibits higher intensity variations among frames than B-mode image [43]. Therefore, the motion estimation using CEUS image registration may be less accurate than that using RF signal tracking or B-mode image registration. This could be a major limitation of this paper. However, our reported reproducibility of strain features seems satisfactory in this study so that we do not need to seek help from extra data (B-mode or RF) at the expense of complicating data acquisition procedures and possibly decreasing frame rate and signal-to-noise ratio of images during dual modality acquisition. Another limitation is that our technique cannot cope with the out-of-plane deformation because it uses 2D image registration. Future work should expand the work to the elastography using 3D image registration on volumetric US.

br Principle of ultrasonic velocity change

Principle of ultrasonic velocity-change method
In general, biological RG2833 consist mainly of water and their ultrasonic velocities increase with rising temperature. On the other hand, the velocities of tissues containing fat decrease with rising temperature. The ratio of ultrasonic velocity change is +1.9m/s in water but it is −4.9m/s in fat, therefore, it may be possible to quantify the percentage of fat on the basis of the change in ultrasonic velocity with temperature. In the liver, the change in ultrasonic velocity with respect to temperature depends heavily on the percentage of fat [16]. Fig. 1 shows the basic experimental setup for the ultrasonic velocity-change method, which consists of a water tank kept at constant temperature, a block containing fat dispersed in water, the ultrasonic linear array transducer and the warming ultrasonic transducer. The ultrasonic linear array transducer transmits and receives the ultrasonic pulse wave. The ultrasonic pulses emitted from the array transducer are reflected from the various boundaries of different acoustic impedance. As shown in Fig. 1, the echo pulses reflected at the boundaries shift according to the ultrasonic velocity change caused by the local temperature rise [17,18] with the warming ultrasonic transducer.
The echo pulses reflected at the boundary surfaces I and II are received by the same transducer. After warming, the echo pulse becomes faster when it propagates in the water-rich domain and reflects back from boundary surface I (Δτ1), but becomes slower when it propagates in the fat containing domain and reflects back from boundary surface II (Δτ2). Consequently, the difference in shift may be expressed as Δτ1+Δτ2. The pulse shift between the bi-border (Δτn) distinguishes the latter shift (Δτn−1+Δτn) from the former (Δτn−1). The round trip time of the echo pulse between the boundaries and the time difference are denoted by τn and Δτn, respectively, so that the velocity change, Δvn, of the warmed region may be represented by where v is the ultrasonic velocity.
The ultrasonic velocity change Δv by the temperature change ΔT is represented as follows,where x is the fat content, (Δv/ΔT) is the temperature dependence of ultrasonic velocity in water and (Δv/ΔT) is that in fat. As (Δv/ΔT)w and (Δv/ΔT)f can be determined in advance, the fat percentage x can be determined from the Δv and ΔT values of the object. Δv can be obtained by the ultrasonic velocity-change imaging method. ΔT is required for the calculation.

Experimental verification for effectiveness of the imaging method

Although Horinaka et al. studied the first system using optical assistance for warming [17,18], we used low frequency ultrasound for warming deeper tissue. The safety of the transducer used for warming has been confirmed and the ultrasonic transducer (1 or 2MHz) is suitable for warming the liver, which is a deep organ. We assume that stable warming is possible at a range of 10cm from the surface of the human body. Regarding the timing of the measurement of the change of ultrasonic velocity, we assessed this before and after the warming process. When we accumulated the data for warming, we found that measurement during cooling was quite reliable. Therefore, we carried out the measurement from the maximum temperature until the normal temperature was achieved. In the animal experiments, the temperature change in the liver was minimal. When the rabbits’ livers were warmed by the ultrasonic transducer, the organs received no damage according to the normal alanine aminotransferase (ALT) value and comparison with sham operation.
The Dixon method of MRI and MRS are widely regarded as the most accurate non-invasive methods for the clinical assessment of hepatic steatosis [21–23]. However, MRI techniques and MRS are somewhat impractical because of their lengthy scan times, their reliance on the compliance of the patient, respiratory artifacts and particular locality, and they typically sample only a portion of the liver. This new methodology based on ultrasonography has the advantage of being non-invasive, with a short scan time, no respiratory artifacts in human patients, occupying little space and assessing a significant proportion of the liver.

In this paper we report a technique which

In this paper we report a technique which simultaneously delivers maps of both specimen thickness and crystal orientation. In ret proto oncogene to orientation mapping in polycrystalline materials, our approach only maps local deviations from a given reference crystal lattice orientation. In most experiments related to the semiconductor industry the orientation of the specimen is fixed, but in order to quantify the strain state of the specimen it is important to measure local changes in orientation. With the approach presented below such local orientation changes can be mapped with a precision of .
In Section 2, we discuss in some more detail the sample preparation and data acquisition, and also the concept and different tools used for data analysis. In Section 3, we present the recovered thickness and orientation maps and discuss possible applications in Section 4.


Results and discussion
However, in contrast to thickness measurement by CBED where the camera length can be chosen large enough to sample even very fine fringes within the CBED disc the method presented here may not be able to reliably determine the thickness in case the rocking curve is not sampled finely enough. As one can see in Fig. 2, at large specimen thicknesses the distance between minima in the rocking curve may be of the order or even smaller than the tilt steps. In that case the intensity variations which enable us to determine the local thickness may not be detectable. Well-controlled finer tilt steps, or a restriction to specimen thicknesses and diffraction conditions where the 2-beam thickness oscillations can still be sampled by the goniometer tilt, could solve this problem.
The excitation of other beams (e.g. higher order Laue zone (HOLZ) reflections) may introduce sharp features in the rocking curves, especially in thick specimen areas. At lower thickness HOLZ lines are not quite as sharp. For silicon and the particular set of parameters applied in this experiment we estimate that the method should work up to a thicknesses of 120nm. In order to be able to detect very low thicknesses the tilt range may have to be increased, since the 2-beam rocking curve, which at low thicknesses becomes very similar to the kinematic rocking curve extends to rather large tilt angles.
The orientation profiles shown in Fig. 4c were integrated in width over 3 pixels and plotted for each Si fin. These orientation profiles show quite interesting behaviors. It seems that some Si fins are bent upward and some downward. The possible explanation of this phenomenon could be deformations of the source-drain structure close to the Si edge. These measurements of an out-of-plane orientation component are complementary to the measurement of in-plane rotation of a similar kind of structure observed by Hytch et al. [29] via dark-field off-axis holography, although those structures were considerably larger. The structure observed in that work [29] was a special test structure where a contact etch stop layer (CESL) induced strain and some deformation of similarly shaped, but much larger fins. The fins in that structure had a length of approximately 300nm, whereas they are only 80nm long and laterally much thinner in the commercial device we have investigated in the present work. From the orientation map one can also see that the orientation varies slightly from left to right. This likely means that the sample is also slightly bent in the horizontal direction. However in the current data set only tilts about the -axis have been measured, and information about any lattice tilt about the -axis is not available. To get the horizontal (-axis-) component of the tilt one needs DF data from another non-collinear reflection. However the sample was bent presumably mostly along the vertical direction, so small deviations along the horizontal directions are negligible. We have also recorded dark-field tilt series for the and reflections. The reflection was not commensurate with the tilt axis. The analysis of that data showed that endothermy was impossible to precisely identify the position of the exact Bragg condition for the reflection. This confirms the obvious fact that for reliable orientation mapping one needs to use reflections for which the product is rather large, i.e. the vector should be nearly perpendicular to the tilt axis or refer to a high order reflection (preferably even a HOLZ reflection).

purchase Erlotinib Hydrochloride br Results and discussion Using offline AFM processing software NanoScope

Results and discussion
Using offline AFM processing software (NanoScope Analysis), a matrix containing an image with 128×512 points was captured with each tip. In these matrices each row represented the step outline measured along the fast-scan direction and every column was the data captured along the low-scan direction. The fast- and slow-scan directions are illustrated in Fig. 6(b). An average step outline was calculated by adding all the rows together and then dividing by the number of columns. A tilt error was caused when the sample was mounted, resulting in a difference between the experimental and theoretical results. To reduce this purchase Erlotinib Hydrochloride error, we chose to study the sidewall component of the step, and the other data of the scanned step were replaced by the horizontal points to eliminate the tilt. Then the modified height points were calculated by FFT to get the amplitude values of the 2nd and 4th harmonics; these two values were substituted into Eqs. (3) and (4) to evaluate the tip radius. The mean solution value of the two equations is used as the estimated value of the tip radius.
The corner radius of the step needs to be known first. A new tip (about 8-nm radius) was used to scan the step structure before evaluating other tips. The corresponding scanned result, as shown in Fig. 7(a), was then analyzed by the above method, resulting in an estimated corner radius of 31.5nm. With this estimated value, the simulation could be conducted. Fig. 7(b) is a comparison of the scanned contour and the reconstructed contour, which shows good coincidence between the two lines. Referring to Fig. 5, the estimated value includes the tip radius and corner radius. Therefore, as the 8-nm tip radius was known, the corner radius of the step can be estimated as 23.5nm. This value was used for amending the following tip characterization.
The estimated radii of tip-1 and tip-2 were 79.2nm and 98.7nm, respectively. The red lines in Fig. 8 depict the simulation contours achieved with the established model with tip radii of 79.2nm and 98.7nm, respectively. Both of the simulation results are in good agreement with the experimental data. However, there are still some errors between them. This may be caused by the assumption that the hemisphere of the tip apex was at a tangent to the tip edges, which may be inconsistent with the actual condition. The arc and edges may intersect, and the shape of the tip apex may be ellipsoidal rather than spheroidal. Moreover, deviation of the tip edge inclination angle α may also cause a difference between the experimental and simulation data. After eliminating the effect of step corner radius, the final evaluated value is obtained as tip-1 55.7nm and tip-2 75.2nm.
To verify Multiforked chromosome method, these two tips were used to scan the characterizer sample RS-15M. Each tip was used to scan two positions on the sample surface to obtain two tip evaluations. With commercial image processing software (NanoScope Analysis), the 3D morphology of the tip apex (Fig. 9) could be estimated from the captured AFM images. The cross-sections (blue lines) along the fast-scan direction (Fig. 6(b)) were selected to estimate the tip radius, coinciding with the FFT characterization direction. The top of every cross-section was fitted with a circle by the least squares fit. Upon fitting, the radii estimates of tip-1 were calculated as 45.2nm (Fig. 9(a)) and 57.4nm (Fig. 9(b)). For tip-2, the corresponding values were 61.7nm (Fig. 9(c)) and 60.4nm (Fig. 9(d)), showing much better consistency. The values obtained with this method were lower than the values estimated with the FFT method. The other direction cross-sections were analyzed as shown in Fig. 9(b) and (d) black lines. For tip-1, there was little difference between radii along the two directions, which indicates the tip apex could be approximately seen as a spheroid. However, tip-2 showed evidence for a worse geometric symmetry – a large difference in radii between the two directions. This blind reconstruction method could be used to obtain visual 3D images of the tips and the radii along different directions, but is susceptible to sharpness features on the sample surface, which should be much sharper than the tip apex. The sharp degree of the feature would result in a misleading evaluation of the tip radius, as shown in Fig. 9(a) and (b). Meanwhile, the image quality obtained while scanning the characterizer sample could also affect the accuracy of the assessment.

Introduction The advent of aberration correction in

The advent of aberration correction in transmission electron microscopy (TEM) has brought about tremendous increases in image resolution, allowing the positions of individual atomic columns to be determined with up to picometer precision [1]. Such local information can prove vital to unlocking the physics behind new materials properties emerging from heterogenous structures such as interfaces, grain boundaries, impurities and other defect structures. A large proportion of the materials of interest today are three dimensional structures of heterogeneous elemental composition, hence a general method to directly determine three dimensional local atomic scale structural and elemental composition is highly desirable.
Bright-field phase-contrast imaging employed in conventional TEM instruments does not provide easily accessible compositional information. Scanning transmission electron microscopy (STEM) however provides chemically sensitive annular dark field (ADF) images. Rutherford scattering from the partially screened atomic nucleus causes the intensity of the ADF signal to increase with the human leukocyte elastase (Z) of the scattering element as approximately , allowing the elemental composition of atomic columns and even individual atoms to be discerned directly from such Z-contrast images. Furthermore, aberration correction in STEM not only significantly increases the lateral spatial resolution, but also provides a shallow depth of field. With just a few nanometers in optimal focus at a time, three dimensional information can be obtained by observing which features are in focus as the probe is focused to different depths. Such optical sectioning has previously been used with Z-contrast imaging in STEM to identify and determine the three dimensional positions of individual dopant atoms [2–7], and to image the core structure and inclination of dislocations [8–10]. However, Z-contrast imaging suffers from an inability to differentiate heavier elements of similar atomic number and very light elements can be obscured by the strong scattering of nearby heavy elements. Hence Z-contrast imaging alone is not sufficient for a general 3D compositional analysis method. For 2D compositional analysis where Z-contrast alone is insufficient, electron energy loss spectroscopy (EELS) is typically employed in conjunction with ADF imaging. Aberration correction has also enabled 2D elemental mapping to be performed with EELS at atomic resolution. Atomic resolution is a necessary condition for nanometer scale longitudinal depth resolution in STEM due to the hollow cone in the three dimensional optical transfer function (OTF) [11]. Operating in a confocal arrangement makes it possible to achieve depth dependent spectroscopic imaging at lower lateral resolution, but this requires significantly more complex and expensive instrumentation [12,13]. The ability to obtain atomic resolution compositional images with EELS now offers the tantalising prospect of spectroscopic optical sectioning without the need for confocal configurations. Furthermore, EELS and Z-contrast imaging can be performed simultaneously and are complimentary, providing the ability to identify different sets of elements. Therefore, optical sectioning performed with both atomic resolution EELS and Z-contrast imaging methods offers a far more general 3D structural and compositional analysis tool than with Z-contrast alone. Theoretical simulations have shown that in principle optical sectioning can be performed with atomic resolution EELS spectrum imaging [14–16], but its experimental demonstration has not previously been achieved.
In this paper, we report the combined EELS and ADF optical sectioning of thin film heterostructures composed of yttria-stabilized zirconia (Y2O3)(ZrO2) (YSZ) and SrTiO3 (STO), a system which has sparked intense debate due to the observation of colossal ionic conductivity at coherent YSZ/STO interfaces [17–27]. Observing a sample with significant islanding, and hence a high level of overall inhomogeneity, we found regions which EELS shows to contain the elements of both YSZ and STO. ADF optical sectioning shows a change in contrast that suggests these regions are composed of YSZ buried beneath STO. Image simulations confirm that the observed contrast variation matches that expected for STO on top of YSZ, and also rule out the possibility that such a change of contrast could be caused just by channeling effects rather than a change in composition. Atomic resolution spectrum images acquired in these regions show a clear depth dependence that agrees with the changes seen in the ADF signal. In particular, a Zr lattice is resolved in spectroscopic optical slices acquired with the probe focused to depths exhibiting YSZ-like contrast in the ADF signal, but when the probe is focused to the entrance surface, where the ADF contrast appears STO-like, the Zr lattice blurs into an area of uniformly high intensity. The results establish the experimental feasibility of 3D elemental mapping with nanometer scale depth sensitivity, and highlight the advantages of spectroscopic optical sectioning. ADF through focal series can show depth dependent changes in composition, but elements of similar atomic number are often indistinguishable. In contrast 3D spectrum imaging provides unambiguous compositional analysis.

br Quantification in a substitutionally

Quantification in a substitutionally disordered structure
The discussion of Fig. 4 in Section 3 focused on the comparison between the models. In this section we use the most rigorous model—the QEP / frozen phonon model—and explore the implications of its predictions for STEM EDX imaging of substitutionally disordered materials.
Fig. 6(a) reproduces the plot from Fig. 4(a) of column-averaged Al K-peak STEM EDX signals from viewed along the [110] zone axis as a function of the number of Al atoms in the column for a 160Å thick sample. The average Al K-peak EDX signal increases with the number of Al atoms in the column. The spread in signal from columns with the same composition but different depth configurations of Al atoms is appreciable. While only a subset of the very large number of possible configurations has been explored, the distributions (most with over twenty different configurations) seem representative. The difference in average number of counts/nA/sr/s between successive numbers of dopants is about 60, but the standard deviation in spread for a fixed number of dopants is also about 60. Consequently, on a column-by-column basis for this 160Å thick sample it all trans retinoic acid would typically be difficult to distinguish configuration variability from genuine differences in composition of ±2 atoms in a 1σ confidence level. The uncertainty will be worse if a stricter 2σ or 3σ confidence level is used. For thicker samples, for example 320Å shown in Fig. 4(a), the uncertainty will be still worse.
It is worth considering what may be done to reduce the configurational variation. Since it is a consequence of channelling, one option is to change the degree of channelling by changing the probe-forming aperture angle, since in periodic samples it is known that the probe-position averaging over a unit cell for larger probe-forming semiangle reduces the effects of channelling [32]. Results for a 30mrad probe-forming aperture angle are shown in Fig. 6(c). Contrary to our objective, it is seen that this has increased the variability due to configurations while reducing the average number of counts, a consequence of the greater probe spreading and cross-talk effect. Another approach is to average over defocus, since in a geometric optics picture this might be expected to give a more uniform weighting of contributions from different depths [83]. Simulations averaging over defocus from 0Å (entrance surface) to −160Å (underfocus equal to the specimen thickness) with a 40Å increment are shown in Fig. 6(b) for the 18.4mrad probe-forming aperture semiangle and Fig. 6(d) for the 30mrad probe-forming aperture semiangle. In both cases, defocus averaging is indeed seen to notably reduce the configurational variation in the signal, potentially improving the precision to ±1 atoms. Table 2 quantifies these tendencies by showing a statistical summary for the case of 20 Al dopants.
The analysis of Fig. 6 takes advantage of the controlled input to the simulations: the number of dopants in each column is known. In real experiments Splice site will not be the case. Fig. 7 looks at the distribution in column-averaged intensities for many columns (specifically 240: five model structures each with 48 distinct columns) comparing a sample of composition , i.e. 50% Al doping, with one of , i.e. 45% Al doping. A 160Å thick sample (i.e. 40 atoms along each column) is again considered, and results shown for (a) the 18.4mrad probe-forming aperture semiangle, and for the 30mrad probe-forming aperture semiangle for (b) the probe focused on the entrance surface and (c) defocus averaged over sample thickness. A statistical summary of the mean and standard deviation of these distributions is given in Table 3. The degree of overlap between the two distributions is very similar in all cases. This occurs because despite the greater precision with which the number of dopants in any individual column can be determined in the defocus average case, Fig. 6(d), under the assumption of random substitutional disorder the number of dopant atoms varies from column to column. For a random distribution of dopants, the number of dopants in a column follows a binomial distribution, which in the present 50% doping in a 160Å specimen implies a standard deviation of three atoms. So, for example, we would be more confident that a column in Fig. 7(c) with 1000 counts/nA/sr/s contains 21 or 22 Al dopants than we would in Fig. 7(b), because the defocus averaging reduces the intensity spread resulting from differences in configuration and thereby improves the reliability of deducing composition from signal strength. But in both cases we could only assess the nominal average composition by averaging over several columns, because otherwise we have no way of knowing how far from the composition\’s expectation value the number of dopants in any given column sits. That said, because the fractional difference in mean intensities between the 45% and 50% Al composition cases is essentially the same for all conditions in Fig. 7, for estimating the all trans retinoic acid average composition there is no appreciable advantage in the more complex conditions of larger probe-forming apertures or defocus averaging: all contain a similar uncertainty as that intrinsically present in the dopant distribution.

p-Cresyl sulfate Watson and Humphreys proposed that

Watson and Humphreys (1997) proposed that the preview benefit involves not only an enhanced ability to detect new items but also the active inhibition of old distractor locations via a spatial memory template referred to as visual marking. According to this perspective, irrelevant information appearing at locations in which old items were displayed previously is inhibited prior to the appearance of new items (Watson & Humphreys, 1997). Thus, irrelevant, old objects previously displayed in the visual field are deprioritized and excluded from the subsequent search. However, several studies have suggested that the preview benefit is due either to automatic attentional capture, precipitated by the onset of new items (e.g., Donk & Theeuwes, 2001), or to mere temporal grouping of new items without active inhibition of old items, resulting in the perceptual segmentation of new and old items during asynchronous presentations (e.g., Jiang, Chun, & Marks, 2002). The inhibition theory differs from the other two theories; in the former, the inhibition of old items plays a role, in addition to the enhanced detection of new items. Although these lines of evidence suggest that onset capture and temporal grouping contribute to preview benefit, in isolation they do not explain the following findings from previous studies: (1) preview benefit can be reduced or abolished by a secondary attention-demanding task imposed during the preview p-Cresyl sulfate (Humphreys, Watson, & Jolicœur, 2002; Olivers & Humphreys, 2002; Watson & Humphreys, 1997); (2) when a dot appears in the search display, it is easier to detect at the location of a new vs. old item (Olivers & Humphreys, 2002; Osugi, Kumada, & Kawahara, 2009; Osugi & Murakami, 2014; Watson & Humphreys, 2000); and (3) color-based inhibition appears to also affect new items of the same color as old items (Braithwaite & Humphreys, 2003; Braithwaite, Humphreys, & Hulleman, 2005), such that targets in the old color are harder to detect compared with those in a new color. Furthermore, a preview benefit also occurs for equiluminant stimuli when the preview period has a duration of 3s (Braithwaite et al., 2006), refuting prior evidence for the absence of a preview benefit with equiluminant stimuli lacking luminance onsets. Such prior evidence has been used as initial support for the onset capture hypothesis (Donk & Theeuwes, 2001). The more recent findings demonstrating a preview effect for equiluminant stimuli are more consistent with the view that the inhibition of old items is a necessary condition for preview benefits.
One important question is whether a preview benefit occurs when an irrelevant transient change is effected in the scene simultaneous with the appearance of the search display. Because such search-task-irrelevant transient stimuli may nevertheless act as a warning signal, conveying information critical for an organism’s survival, it is reasonable to suggest that attentional resources are automatically allocated to detect such a change, thereby attenuating any preview benefit in the current search task. Previous studies (e.g., Watson & Humphreys, 1997, 2002) have demonstrated that preview benefits disappear when the shape of old items is altered during the preview period, but remain during changes in color or luminance, and when old and new items differ in color. These findings suggest that transient motion, or positional shifts accompanying abrupt changes in the shape of old items, attenuate preview benefits. Furthermore, recent studies suggest that the preview benefit remains even when the shape of old items changes, provided that these changes involve either eye blink (Irwin & Humphreys, 2013; von Mühlenen, Watson, & Gunnell, 2013), occlusion (Kunar et al., 2003), or transient masking (Watson & Kunar, 2010). Osugi, Kumada, and Kawahara (2010) demonstrated that preview benefits persist during shape changes if semantic information pertaining to the items is retained. Taken together, this literature points toward a role for top-down processing in the maintenance of preview benefits, despite the presence of disruptive, bottom-up signals (see also Osugi & Kawahara, 2012).

As no commercially accountable antibodies for adrenoceptor subtypes are available

As no commercially accountable rad51 inhibitor for α1-adrenoceptor subtypes are available, we used the tissue-segment binding method with the α1A subtype highly selective isotope [3H]-silodosin to specifically quantify this subtype at the protein level in the rat ventral prostate. We found that despite the great decrease of the ventral prostate weight, there was no significant change in the relative α1A adrenergic density, but a contrarily marked decrease was observed in the total α1A protein level in the whole ventral prostate. This is quite different from the study by Lacey et al, in which there was an apparent relative increase in α1-adrenergic density, but no significant change in the absolute density of α1-adrenoceptors in the rat whole ventral prostate 5 days after castration. We also found no significant changes of phenylephrine-induced contractility when normalized to the strip weight or contraction potency detected after dutasteride treatment, which is also different from the 2 studies of the adrenergic contractility in castrated rats. A previous study showed that in a rat ventral prostate model, castration caused decreased nerve-mediated contractions at low frequencies, but it also showed a tendency to increase the contractions at high frequencies. We therefore further evaluated the effects of dutasteride on nerve-mediated contraction, but we also found no marked changes at any of the frequencies tested.
Some studies showed that treatment with finasteride caused epithelial atrophy, with little if any effect on the prostate stroma, and the treatment markedly increased the ratio of stroma to epithelium. However, Prahalada et al reported that a 6-month administration of finasteride resulted in significant decreases in the total number of both epithelial and stromal cells per gland in the ventral lobes of the prostate. In our present study, although dutasteride treatment caused a very large decrease in the ventral prostate weight, there was still no significant increase in the relative expression of the α1A subtype at either the mRNA or protein level to be found. Moreover, the total protein amount of the α1A subtype in the whole ventral prostate was significantly decreased.
As the α1A subtype exists predominately in the stromal component of the prostate, and the binding affinity of the α1A subtype does not change (because there was no change of pA2 value for silodosin), it is reasonable to speculate that dutasteride caused the decrease in the stromal component along with the atrophy of epithelium. Therefore, the total α1A protein level decreases along with the reduction of the stromal component. Interestingly, the study by Lacey et al showed that the stromal cells remained virtually unchanged 5 days after castration, and the total protein expression of α1-adrenoceptors did not change even when the ventral prostate weight decreased to a greater extent than that caused by 2 months of dutasteride treatment in the present study.
These differences showed that compared with castration, dutasteride also has specific effects on the proliferation of stromal cells in the ventral prostate. Accordingly, unlike castration, dutasteride does not cause a relative increase of α1A-adrenergic receptor but reversely decreases the total protein amount of this subtype and then in turn suppresses its mediated maximal contraction in the whole ventral prostate as observed in this study.

The 5α-reductase inhibitor dutasteride showed distinctive effects on the expression of α1-adrenergic receptors and the related contraction in the rat ventral prostate compared with previous reports on castration. Dutasteride treatment caused no significant changes in the relative adrenergic density of α1A-adrenergic receptor and contractility, whereas it greatly decreased the total protein expression of this subtype and its mediated maximal contraction in the rat whole ventral prostate. This characteristic suggests that dutasteride does not interfere with α-adrenergic blockers, but otherwise has beneficial effects on their actions. Therefore, the long-term administration of the combination of dutasteride with an α-adrenergic blocker might be a better choice for the treatment of lower urinary tract symptoms due to BPH.