For example Mohite et al

For example, Mohite et al. [9] prepared Au doped TiO2 thin films by spray pyrolysis, decreasing the band gap and increasing the photoelectrocatalytic degradation of benzoic ochratoxin a under UV light illumination of 49%. Even metal oxides such as WO3 improve the photocatalytic activity of TiO2 under solar light, as recently reported by Hunge et al. [10,11].
Seery and co-authors report Ag modified TiO2 with increased visible light activity compared to bare TiO2[12] due to the surface plasmon band of Ag, which absorbs in the visible spectrum [13]. The scientific literature is rich of procedures and data on the synthesis of Ag NPs supported on TiO2. Examples include impregnation from Ag colloidal dispersions [14] or from Ag inorganic salts [15,16], electrostatic self-assembly [17], and photo-reduction of Ag salts [18]. Only few manuscripts deal with the ultrasound-aided synthesis of supported Ag particles. Liu et al. synthesized nanofiber-supported Ag particles in the presence of different reducing agents, including short-chain alcohols and nitrogen compounds [19]. Ye at al. deposited Ag seeds on the surface of SiO2/TiO2 core–shell composites in a multi-step process, growing them to the structure of Ag shells with formaldehyde as a solvent [20]. However, none of them specifies the ultrasound (US) operating conditions (e.g., power and frequency). Moreover, they both deposit Ag in the presence of organic solvents.
Sakkas et al. report the decoration of M- or MO-NPs by means of US in aqueous or organic solution containing dispersed ceramics or polymers in powder form [21].
US has a potential to impact every stage of the preparation of a material in liquid phase. US produces nanomaterials in amorphous state (due to the very high cooling rates) [22], or stabilizes crystalline phases [23] which is relevant to fields such as catalysis, magnetism and coating processes. US generates shock waves that facilitate coating and insertion/intercalation processes and improves the distribution of the active phase on a support [24]. The mechanical waves increase nucleation production rate (i.e., in the sol–gel process) and develop defects and deformations of solid surfaces, creating additional surface area and exposing active and selective catalytic sites [25]. Despite its undisputable advantages, US is a technique fossil record is still unexplored in the synthesis of an enormous number of materials. Ultrasonic-synthesis may refer the manufacture of inorganic and organic materials or their deposition on supports, including metal oxides [21], and metallorganic compounds [26]. Other US-aided techniques comprise the modification of the structure and/or the morphology of already formed materials, for instance through the re-dispersion of the supported phase [27].
We recently made the choice to adopt micro-particles [28] because nanopowders exhibit potential risks in terms of dispersibility [29], ecotoxicity [30], persistency [31], and bioaccumulation [32]. The International Agency for Research on Cancer (IARC) classified ultrafine TiO2 as possible carcinogenic to humans (IARC, 2010). Papers reporting synthesis of micrometric particles of TiO2 are still few. Liu et al. reported the synthesis of porous TiO2 microsphere [33]. However all the other data refer to sub-micrometric powders [34,35]. We first pioneered the photocatalytic application of commercial micrometric TiO2 and proved that is as efficient as the nanometric TiO2[36,37]. Finally, in a recent work, we synthesized Cu NPs supported over micrometric TiO2: while the bare micro-metric TiO2 is inactive under visible light, the 40% by weight Cu-TiO2 sample degrades 28% acetone in 6h [38].
Here, we report the one-step US-assisted synthesis of Ag NPs. Our work is innovative for the following aspects: i) We are the first to report the ultrasonic synthesis of Ag-TiO2 and we explicit US operating conditions; ii) Water is the solvent, which eliminates organic solvent disposal issues; iii) The support are micro-sized TiO2 spheres as an alternative to nano-sized TiO2, differently from the quasi-totality of the reported data.

JNJ26481585 br Thickness shear trapped modes for acoustic wave filter

Thickness shear trapped modes for acoustic wave filter design
The discovery and discussions on the trapped modes offer opportunities for designing various acoustic devices. An example of an acoustic filter is given hereafter, with its thickness changing sectionally along ±x3 directions, as shown in (a). The thickness of the plate is 2h0, 1.8h0, 1.6h0, 1.4h0, 1.2h0 and h0 at , , , , and , respectively. Correspondingly, the values of in each sub-regions are 1, 1.111, 1.25, 1.429, 1.667 and 2. For simplification, we use Eq. (12) and the transfer matrix method during the following numerical simulation. For FEM simulations, two additional perfect match layers (PMLs) are applied as extended domains at the region to prevent wave reflections [9,32], shown in (b). We mainly focus on the JNJ26481585 trapping phenomenon caused by thickness changes, so that the non-dimensional frequency will be limited to .
For every flat sub-section in the region of , Eq. (12) is the exact solution for the thickness shear waves. However, for the region of , either A′ (for ) or B′ (for ) is used to describe the amplitude of the outgoing waves. At every interface between each adjacent sub-regions, the continuity of displacement and the moment of shear stress is adopted so that an implicit frequency equation about Ω can be obtained. Fig. 8 shows the variation pattern of Ω of different thickness shear modes existing in the structure designed with the length parameter b. All these frequencies of the thickness shear vibration initiate cut-off frequency of the unbounded quartz plate with thickness of 2h0 (=2), and approach the value equalling to =1 with the increasing b. This means the longer embed thinner portion decreases the resonance frequency, with more modes trapped in this region. The effect is the same as that of inertial mass layer, attached on the surface of quartz plate [33]. On the other hand, higher modes appear periodically with the increasing b, which can be seen from Fig. 8. For instance, the second mode appears at b=0.26h0; the third one at b=0.45h0; the forth and fifth modes at b=0.66h0 and b=0.85h0, respectively. The period Δb is about 0.19h0.
Fig. 9 gives the displacement distribution for different trapped modes, marked from A to K in Fig. 8, along x3 direction when b=2h0. The amplitude has been normalized such that the displacement of the left- or right-hand-side traveling wave in the center region is equal to one. We can see the inner resonance nature of the patterns, with the internal vibrational magnitude of higher modes larger than that in the center region. This phenomenon is in accordance with the work by Cao et al. [30] and Hussein et al. [31]. It can also be concluded from Fig. 8 that, if a thickness shear wave is excited in the central region, i.e., , the one with higher frequency can propagate longer distance away from the center. Taking Mode E for example, its resonance frequency is Ω=1.5149, which is located between the two corresponding cut-off frequencies =1.4285 (i.e., the thickness is 1.4h0) and =1.6667 (i.e., the thickness is 1.2h0). Hence, the wave can be viewed as a propagation wave with its displacement represented by sine and cosine functions in the region . However, when the wave travels in the region , the amplitude decays exponentially during propagation due to the imaginary wavenumber. In contrast, for Mode A, Ω=1.0593, which is larger than =1 (i.e., the thickness is 2.0h0) and smaller than JNJ26481585 =1.111 (i.e., the thickness is 1.8h0), the vibration is reduced evidently only after the wave arrives at . Other waves in Fig. 9 behave similarly. The displacements of Mode J and K do not decay to zero at because higher frequencies lead to slower decaying rate, as shown in (a). As comparison with Fig. 9, Fig. 10 gives the displacement distribution of different trapped modes exported by FEM under the same condition. A slight difference in the resonance frequencies calculated by FEM and theoretical analysis exists, which again is attributed to the application of an equivalent continuity of shear stress moment during theoretical treatment. Nevertheless, the energy trapping phenomenon in Fig. 10 is basically identical as shown in Fig. 9.

br Result and discussion Because

Result and discussion
Because of micro-cracks, the effective material parameters (effective moduli, effective Poisson ratio) of elastic solids have subtle changes under a dynamic loading, which can lead to a slight change of the phase velocity of Lamb waves after they ion channel pass through the micro-crack damage zone [14]. Meanwhile, because the wavelength (13–53mm) of the low-frequency S0 mode is much larger than the crack length (10–200), most of the waves can pass though the micro-crack damage zone (transmitted waves), and only a very small portion of the waves are reflected by the micro-cracks (reflected waves). Both of the transmitted and reflected waves may contain the second harmonic waves. To the best of our knowledge, there is no relevant work to analyze this problem. Therefore, we set two locations in the FEM model to collect and analyze the transmitted waves and reflected waves respectively.

A numerical model containing randomly distributed micro-cracks was constructed to investigate the propagation phenomenon of low frequency S0 Lamb waves by a Monte Carlo simulation method. Using the S0 mode as fundamental waves, the ultrasonic nonlinear effect in terms of second harmonics caused by the micro-cracks was explored in details. The following conclusions have been drawn:
First, when the low frequency S0 mode is used as fundamental waves, there was no second harmonic wave in thin plates without micro-cracks. It indicates that the low frequency S0 mode can be used as fundamental waves to effectively identify micro-cracks in thin plates. Moreover, since the S0 mode is the only mode existing within the low excitation frequency domain, i.e., 100–400kHz, this technique can effectively avoid the interference of high-order modes, e.g., S1 and S2, thus increasing the signal-to-noise ratio.
Second, the influence of micro-cracks on the propagation of the S0 fundamental wave was insignificant although its normalized phase velocity decreased linearly with the micro-crack density. At the same time, the equality condition between the phase velocity of the fundamental wave and that of the second harmonic wave could be achieved within the low frequency domain, e.g., 100–800kHz, which makes the quantitative analysis of the relationship between the generated second harmonics and the extent of material nonlinearity possible.
Third, we systematically investigated the relationship between the acoustic nonlinear parameter and some key factors, i.e., micro-crack density, excitation frequency, friction coefficient of the micro-crack surfaces, and propagation distance in the cracking region. The results reveal that, the acoustic nonlinear parameter in the y-axis was much stronger than that in the x-axis; and Minicell was linearly proportional to the crack density and propagation distance of waves in the cracking region. The acoustic nonlinear parameter increased significantly with the excitation frequency. However, it was not correlated with the friction coefficient of the micro-crack surfaces. Therefore, the acoustic nonlinear parameter can be used to effectively characterize the degeneration of material properties caused by micro-cracks. Furthermore, a proper increase of the excitation frequency can generate more significant second harmonics and improve the efficiency of this technique.
Finally, weak reflected waves in the x-axis could be induced by micro-cracks. We found that the region containing micro-cracks could be located by detecting these reflected waves at different positions. Although the intensity of the reflected waves was lower than that of the transmitted waves by one order of magnitude, these reflected waves contained more significant second harmonics. This finding provides a theoretical foundation for effective detection of micro-crack locations. We will further verify the results obtained in the present study by using an experimental measurement technique similar to that [19].

Breast cancer is the most common cancer and the second leading cause of cancer death after lung cancer among women worldwide. Early detection is the most effective way to reduce the mortality. The best practical approach to detect breast cancer is breast imaging by which radiologists can detect cancer\’s symptoms in early stages [1].

br Discussion The contrast shown in Fig b is very

The nucleoside analogs shown in Fig. 1(b) is very much like crystallographic contrast obtained using a BSD. Since no such strong orientation contrast detected by a secondary electron detector has been reported before, it is necessary to show that it is orientation contrast. When comparing Fig. 1(b) to its OIM, Fig. 1(c), it is clear that the grains having bright contrast in Fig. 1(b) are close to <111> orientation, which are the blueish grains in Fig. 1(c), the grains having dark contrast are close to <100> orientation, which are the reddish grains in Fig. 1(c) and the grains having gray contrast are close to <110> orientation, which are the greenish grains in Fig. 1(c). Note that there are several dark contamination stains in Fig. 1(b) which were formed during specimen preparation.
Because strong orientation contrast detected by a secondary electron detector is uncommon, the possibility that this contrast came from SE2 (i.e. secondary electrons generated by back scattered electrons) has to be considered. If the orientation contrast obtained is caused by SE2, it will be similar to the contrast detected by the BSD, so that individual grains will show similar intensity, which would vary with tilt angle in the way that BSD does. Comparing Fig. 2(a) and (c), it can be seen that many grains and twins show opposite intensities, and comparison of Fig. 3(a) and (b) with Fig. 3(c) and (d) shows that the influence of tilt angle is very different. These observations show that the contrast seen in Fig. 2(a) and in Fig. 3(a) and (b) is not from SE2 and that the orientation contrast detected by the in-lens detector is caused mainly by primary secondary electrons, the so-called SE1 [6].
Fig. 7(a) shows the orientation contrast obtained at 5kV from an area of a specimen. To reveal the surface morphologies of the grains showing different contrast, a triple junction of three grains, A, B and C, having different image intensity levels shown in Fig. 7(a) was enlarged in Fig. 7(b). From Fig. 7, it can be seen that the higher the image intensity of the grain in Fig. 7(a), the rougher the surface is. This can be explained by the yield of secondary electrons. Compared to a smooth surface, a rough surface has a larger fraction of surface area inclined to the incident electron beam, since secondary electron yield increases as the inclination angle of a crystal surface is increased [2,7], therefore, a grain with a rough surface will have bright contrast. In addition and closely related to this effect, it is clear that many low energy secondary electrons need to travel very small distances to escape from a sample if it has a rough surface. If the roughness is dependent on the surface normal the intensity will change across grain or twin boundaries. The level of surface roughness shown in Fig. 7 clearly does vary with orientation, as required and this roughness is typical of that found on electropolished samples; electropolishing is effectively controlled etching and thus tends to lead to roughness which is orientation-dependent although the level of roughness is well below that in etched samples.
In order to further confirm the role of surface roughness, samples have been carefully mechanically polished since the surface roughness of all grains in a mechanically polished specimen will be very similar. Fig. 8 shows the images taken from a mechanically polished specimen, which was final polished using 0.05 μm alumina. Fig. 8(a) was obtained under the same imaging conditions (in-lens detector) as that of Fig. 1(b), the only difference is the brightness setting of Fig. 8(a) was 33.6%, which is slightly higher than B=32.3% in Fig. 1(b). It can be seen that only very weak orientation contrast is obtained from the mechanically polished specimen, with the contrast in Fig. 8(a) being much lower than that in Fig. 1(b). Fig. 8(b) and (c) are the images from the same area detected by the E–T detector and BSD, respectively. Close examination of individual grains in Fig. 8(a)–(c), shows that the changes in intensities between grains are similar (but far less obvious in (a) and (b)) showing that the contrast in (a) and (b) is crystallographic contrast caused by SE2. A location, which has four levels of image intensities, (arrowed in Fig. 8(c)), was enlarged under the conditions that a high image resolution could be obtained, (see Fig. 8(d)); the same surface roughness was found in grains having different image intensities. Fig. 8(e) was imaged using the BSD detector from the same area as shown in Fig. 8(d). These observations confirm the expected difference between SE2 images and those reported in this paper using the in-lens detector to image electropolished samples.

br Non circularity of the surface state Visual inspection of

Non-circularity of the surface state
Visual inspection of the Fermi surface contour in Fig. 5a shows a perfectly circular shape of the surface state. For the Shockley surface states on the [111] fcc surfaces, the prototype of a two-dimensional nearly free e3 ligases gas, this is the expected result. On the close packed surfaces, the corrugation of the electron density is smeared out and an in-plane gradient of the potential becomes negligible. The surface state then can be effectively described by an isotropic parabolic dispersion of a free electron only characterized by a modified effective mass . This is not the case when a considerable in-plane gradient of the potential is present, for instance for various surface alloys like Bi/Cu(111) or Bi/Ag(111), where the six-fold rotational symmetry of the surface layer is clearly observed in the Fermi surface contour [31,50,51].
A precise measurement of the rotational symmetry of the Shockley surface state by conventional ARPES by scanning the sample or analyzer is complicated by the mechanical movement involved. By contrast, the present momentum microscope acquires the complete Fermi surface contour simultaneously. Fig. 5d shows the measured radius of the outer (solid line) and inner (dashed line) ring of the surface state, obtained from the center positions of the Voigt profile fit, respectively. The in-plane angle is measured with respect to the horizontal direction. We find a non-circularity of both surface state rings with an amplitude of peak-to-peak, and a threefold 120° periodicity. An estimate of the statistical uncertainty of the radius measurement is given by the scatter of individual data points and the agreement between the inner and the outer surface state ring. Here, this uncertainty is of the order peak-to-peak, and clearly distinguished from the observed three-fold modulation.
Instrumental distortions can be excluded as the source of the three-fold radial symmetry for several reasons: first, the electron optical system does not contain elements with a three-fold symmetry. The major breaking of the rotational symmetry is introduced by the energy filter, which however might give rise to a two-fold astigmatism along the k axis. Such contributions can be clearly separated from the observed three-fold periodicity. More importantly, we additionally checked that the three-fold periodicity of the surface state radius is aligned with the crystal axes of the sample. For this, the Au(111) sample was mechanical rotated, while all other parameters of the instrument were left unchanged. We found that this rotation leads to a corresponding phase shift in .
We conclude that the variation of the in-plane momentum follows the three-fold bulk symmetry. A six-fold symmetry from the surface layer, as outlined above, is not clearly observed, but might be present below the noise level. We therefore relate the observed deviation from a perfect circle to the interaction between the surface state and the edge of the projected bulk band gap. Previously, a deviation from the free-electron description due to hybridization with bulk states could only be observed experimentally when the surface state of Cu(111) approaches the edge of the band gap above the Fermi level [52]. A similar behavior was also predicted for Au(111) [21]. At the Fermi level, however, the deviation from the free-electron gas becomes small, in general. Our results provide a quantitative estimation for limits of an isotropic free electron model of the Shockley surface state, for the first time.

Spin resolved results
Spin resolved photoelectron momentum distributions were recorded by introducing a spin polarizing electron mirror into the electron optical path after the energy filter. The principle of spin filtering of a two-dimensional electron distribution was introduced earlier using a W(100) scattering target [32]. Spin contrast is obtained due to the spin dependent reflectivity of low-energy electrons at the non-magnetic surface of the scattering target which is governed by spin–orbit coupling, such that electrons with opposite spin see different scattering potentials, leading to different scattering amplitudes [53]. Image information is transmitted in the momentum conserving (00) LEED beam. Previous measurements showed that scattering energies of 26.5eV and 30.5eV with a spin sensitivity of 42% and 5%, respectively, are efficient working points for a clean W(100) scattering target [32,33]. Using an Ir(100) single crystal, a sharply peaked high spin asymmetry and reflectivity was found at scattering energies around 10eV and a rather broad asymmetry maximum around 40eV for the clean 5×1 reconstructed surface [54]. For a pseudomorphic monolayer of Au on Ir(100), experimental data and theory from Ref. [34] also find an asymmetry maximum at 40eV scattering energy under an angle of incidence of 45°, while the low energy region was not explored, so far. In addition, the reported long-term stability of the Au/Ir(100) surface of several weeks makes this system an interesting candidate for the imaging spin-filter of the present momentum microscope.

Fig shows the band structure

Fig. 6 shows the band structure and the density of states (DOS) of α-Al2O3 calculated using the modified HSE06 hybrid functional. Typically, relatively flat valence bands appear in metal oxides such as α-Al2O3 because the valence electrons strongly localize as flunixin meglumine p-states around the oxygen (anion) in the ionic crystals. These localized valence electrons cause the bands to be flat in reciprocal space, and the energy dispersion of the valence electrons for a momentum change becomes small. When we consider an flunixin meglumine excitation from the flat valence band to a certain k-point in the conduction band, the transition energies in an optical excitation, ΔE(0), and in an excitation by an electron, ΔE(q), are almost equal, as shown in Fig. 7. Thus, the imaginary part of the dielectric function in α-Al2O3 should refer to a joint density of state (JDOS), which is represented approximately by the convolution between the partial DOS of the valence band in a p-orbital and the partial DOS of the conduction band in an s-orbital [35]. A comparison of the imaginary part of the dielectric function and the JDOS is shown in the Fig. 8, and we can see a good coincidence.
Further, we examined the SSD obtained in the 60kV TEM, wherein the Cerenkov radiation did not occur in the energy range lower than the bandgap. However, the real part of the dielectric function of α-Al2O3 has a peak around 10eV and the velocity of the electron exceeds the speed of light near this energy. Furthermore, the influence of the light-guided mode may appear with an acceleration voltage less than the Cerenkov limit. Therefore we calculated the SSD based on the Kröger equation [12,15] using the optical measurement data for the dielectric function, and these calculated SSDs are plotted in Fig. 9 with the experimental data. The blue line is the calculated value considering only the volume loss, whereas the red line is the value including both the volume and surface losses. It can be seen that the influence of surface losses in this experimental condition is almost negligible. The experimental data agrees well with these SSDs, and therefore the Cerenkov radiation and light-guided mode were sufficiently suppressed in α-Al2O3 by using the 60kV TEM.
As described above, the difference method has been shown to be useful for measuring the dielectric function under Cerenkov radiation conditions. However, because it is necessary to remove the direct spot in the difference method, a restriction on the convergence angle occurs during nano-beam analysis using a convergent electron beam. For instance, in the recently developed spherical aberration-corrected STEM, a convergence semi-angle of over 20 mrad has been achieved, but the difference method cannot be used because of overlap of the diffraction disks. Therefore, using an acceleration voltage below the Cerenkov limit becomes a better choice to acquire the low-loss spectra at a higher spatial resolution. We consider that the present technique is effective in a high-k material; however, Zhang et al. have reported that the dielectric function of diamond obtained by the difference method did not completely coincide with the optical data [2]. It has been suggested that the difference method could not completely remove the relativistic effects, i.e. the Cerenkov radiation and retardation effects, because the maximum value of the real part of the dielectric constant of diamond is roughly twice that of α-Al2O3. Another reason is that they have acquired the spectra using a relatively large collection semi-angle, which was not sufficiently small because the energy bands of the diamond are not flat, as they are in α-Al2O3. It is expected that the finite momentum transfer strongly affects the shape of the dielectric function of diamond. This issue will be investigated in detail in our future work.

We investigated the efficacy of the difference method for the measurement of the dielectric function of α-Al2O3 by EELS. The dielectric function measurement failed owing to the presence of Cerenkov radiation when using 200kV TEM, whereas a good agreement of the dielectric functions obtained via 60kV TEM and the optical data was indicated. Even when the accelerating voltage of the TEM was set to 200kV, the dielectric function obtained using a combination of EELS and the difference method agreed well with those of 60kV TEM and optical measurements. This combination of the EELS and the difference method in the NBD mode can derive an accurate dielectric function with superior spatial resolution regardless of the occurrence of Cerenkov radiation. Although very good agreement between the optical data and the results obtained by the difference method can be achieved, avoiding relativistic losses completely is still an even better choice.

A Synchrotron in a Microscope how prescient and insightful

“A Synchrotron in a Microscope” – how prescient and insightful have these words proved to be. The latest SuperSTEM instrument, a monochromated Nion UltraSTEM100MC ‘HERMES’ delivered in early 2015, not only incorporates an advanced Mark IV Cs probe corrector, but also a high-energy-resolution monochromator, which enables spectroscopy experiments in the sub-10meV caspase pathway resolution regime [7]. This instrument now arguably surpasses the capabilities of synchrotron beamlines, in some specific cases at least.

Aberration diagnosis
It is generally accepted that the lack of fast and automated aberration diagnosis methods (or auto-tuning) was one of the main factors that prevented for nearly fifty years the successful implementation of aberration correction in the TEM (for a review and discussion of other factors, see e.g.[8] and references therein). Famously, this is in spite of the general principles having been outlined by O. Scherzer as early as 1947 [9]. The strong emphasis placed by Krivanek et al. on the role of software designed to measure and adjust the aberrations in early reports of the working STEM QO correctors is striking [6,10,11]. Without them, “one is faced with a fuzzy image, a large number of controls and no useful procedure for making the image sharper” [6]. The drive towards automation is best exemplified through Ondrej Krivanek\’s own earlier contributions to the field of aberration measurement, long before the inception of the Cambridge QO Cs correction project. Single diffractogram analysis to determine defocus and Cs[12], or repeated (no doubt hurried!) trips from the microscope room to the optical bench via the dark room in order to analyse diffractograms and stigmate a high voltage instrument [13], eventually led to some level of automation thanks to the advent of charge-coupled devices (CCDs) [14]. The original tuning algorithm for the Nion prototype corrector described in the EMAG1997 conference proceedings is closely related through reciprocity to the procedure described in the latter, using tilt-induced shifts (TIS) in a series of scanned bright field images to derive the aberration function, as illustrated on Fig. 1[14,15].
Attempts to devise faster, more precise, more universal diagnosis tools for STEM to replace the original TIS method provided the basis for at least two generations of doctoral students at the Cavendish Laboratory in Cambridge [16,17] but also elsewhere [18], continuing the effort that had been initiated as part of the Cs corrector development project. Reviewing the many contributions to the field would no doubt be beyond the scope of this article and interested readers are encouraged to consult A.R. Lupini\’s masterful treatment of many aspects of aberration measurement [19], including his own contribution based on the analysis of a series of Ronchigrams. The realisation that the Ronchigrams’ local magnification could be linked directly to the second derivative, or Hessian, of the aberration function [20,21] is still to this day at the heart of the tuning algorithms employed on Nion microscopes [22]. Interestingly, and despite successful attempts to devise techniques that can be applied to crystalline materials [19,23], most algorithms deployed in aberration-corrected STEMs today still suffer from a lack of universality. They often require a very specific object type to converge satisfactorily, either some amorphous area of the sample potentially far away from the region of interest, or a dedicated tuning sample altogether [18]. It is perhaps a testament to the stability of modern correctors that the implementation of universal tuning algorithms has not been pursued more actively, the existing solutions clearly providing enough usability for most applications. The ‘achromatic line’ approach of Ramasse et al. [23] for measuring non-round aberrations from on-axis crystals for instance, although fully functional and tested on SuperSTEM instruments, was never practical or fast enough to supplant (or indeed complement) the main Ronchigram-based autotuning routine: Fig. 2.

br Conclusions We have investigated effects of

We have investigated effects of cueing in AwD using two tasks where effects were expected to beneficial (Experiment 1) or detrimental (Experiment 2). In Experiment 1, AwD showed normal effects of cueing in a probe detection task. Like controls they ldk378 benefitted from using a cue circle to orient and distribute attention. Like controls, they performed better when the probe was included in the circle, showed effects of eccentricity – performing best with probes at central locations and increasingly worse with probes at farther locations, and showed effects of SOA – performing best when the cueing circle was shown earlier, thus allowing more time to prepare. In addition, AwD showed a stronger effects of SOA at far eccentricities when more time was needed to move attention and stronger effects of cues on the left, possibly because here attention was weaker. These results show that AwD are perfectly able to use cues to direct and distribute attention (see also Cassim, Talcott, & Moores, 2014; Moores, Cassim, & Talcott, 2011). In Experiment 2, AwD, in fact, showed stronger effects of cueing than controls. In a texture detection task, they benefitted from cues even at central locations where restricting the focus of attention should have actually hindered performance. We believe that both sets of results are best interpreted by assuming that AwD suffer from weaker attentional resources or a weaker spotlight of attention. According to this hypothesis, AwD would have no difficulties to orient or focus attention using cues, consistent with the results of Experiment 1. Instead, difficulties will arise when there are not enough attentional resources to split attention to different locations or when attention cannot be further restricted (e.g., see Romani et al., 2011). This limitation in restoring the focus of attention would result in net positive effects of cueing in Experiment 2: cues orient attention to the right area, but attention is not restricted to the point where this is detrimental for texture detection.
More broadly, our results are consistent with theories which see attentional limitations as an important source of difficulties in developmental dyslexia. Since neither letters nor complex stimuli were used in these experiments, phonological difficulties in AwD are unable to account for the results. One may note that we have investigated partially compensated adults with dyslexia rather than children. Our results and interpretations, however, are broadly consistent with a number of findings from the literature, both on children (e.g. Bosse, Tainturier, & Valdois, 2007; Lassus-Sangosse, N’Guyen-Morel, & Valdois, 2008; Lobier, Zoubrinetsky, & Valdois, 2012; Valdois, Bosse, & Tainturier, 2004) and AwD (Cassim, Talcott, & Moores, 2014; Judge, Caravolas, & Knox, 2007; Judge, Knox, & Caravolas, 2013; Moores, Cassim, & Talcott, 2011; Romani et al., 2011). A number of studies have reported impaired performance in processing multi-element arrays in dyslexic children (Hawelka & Wimmer, 2005) or AwD (e.g. Hawelka, Huber, & Wimmer, 2006; Romani, Tsouknida, & Olson, 2015). Bosse, Tainturier, and Valdois (2007) argued there is a narrow attentional window in dyslexia in terms of the amount of information Signal sequence can be processed at once from a briefly presented display. Romani et al. (2011) have shown that AwD have a reduced capacity to split attention in a number of distinct spotlights.
The idea that AwD might have a weaker attention spotlight has important implications for reading. Rayner et al. (1989) reported a case study of an adult with developmental dyslexia who read more successfully when letters outside of a small centrally fixated window were replaced with Xs (see also McConkie & Rayner, 1975). Spinelli et al. (2002) asked CwD and controls to say whether two words presented sequentially on a screen were the same or different and measured vocal reaction times. They showed that CwD were more detrimentally affected than controls by surrounding ‘crowding’ stimuli. A second experiment showed an improvement in word reading with increased inter-letter spacing. Benefits of increased letter spacing were also shown in young readers and CwD by Perea et al. (2012) and Zorzi et al. (2012). Similarly, people with dyslexia find easier to read text when words are displayed one at a time or one line at a time (e.g. Hill & Lovegrove, 1993; Lovegrove & MacFarlane, 1990; Schneps, Thomson, Chen, et al., 2013; Schneps, Thomson, Sonnert, et al., 2013). Franceschini et al. (2012) showed how performance on visual attention tasks in pre-school age Italian children can be used to predict reading acquisition two and three years later. All of these studies are consistent in pointing to a visuo-attentional impairment in dyslexia. Solutions, however, are more difficult to devise. Crutch and Warrington (2009) reported two cases of acquired dyslexia caused by posterior cortical atrophy that showed large negative effects of flanking and positive effects of spacing in letter identification tasks. However, increasing letter spacing within words had only limited benefits for reading because although individual letter ldk378 identification was improved, whole word reading was negatively affected. This exemplifies the difficulty of finding solutions for a weaker attentional spotlight and increased crowding effects in dyslexia.

Importantly recent work shows that MT center surround

Importantly, recent work shows that MT center-surround mechanisms are not fixed but adapt to changing stimulus conditions. Specifically, surround suppression can shift to facilitation at low-contrast (Pack et al., 2005) or when motion in the receptive field center is ambiguous (Huang, Albright, & Stoner, 2008; Huang et al., 2007)—all conditions where motion integration is beneficial. Consequently, perceptual mechanisms that critically depend on surround suppression should also exhibit analogous stimulus dependency. This hypothesis is explored in Section 3.1.

Perceptual correlates of surround suppression
Given the prominent role of surround suppression in neural mechanisms of motion processing, we should to expect to find observable perceptual correlates of surround suppression (see Sections 3.2 and 3.4 for detailed considerations of issues behind this linking hypothesis). Indeed, psychophysical studies have reported results consistent with surround suppression. Sachtler and Zaidi (1995) showed that detection of motion-defined boundaries could be explained by eccentricity-dependent center-surround mechanisms. Verghese and Stone (1996) found that speed discriminations improved when a single large moving stimulus was divided into several smaller stimuli. The authors suggested suppressive surround mechanisms as a possible explanation. Derrington and Goddard (1989) found OF-1 Supplier that direction discriminations of brief, large gratings worsened as the contrast increased. This result is consistent with contrast-dependent surround suppression (Pack et al., 2005), although the authors did not vary stimulus size and did not consider size-dependent explanations. Murakami and Shimojo (1993) investigated induced motion in stationary stimuli presented within a large patch of moving dots. They found that motion induction (i.e., motion contrast) transitioned into motion assimilation when stimulus contrast and size were reduced or when the stimuli were shown in the visual periphery. This finding shows that motion induction changes to spatial summation under low visibility conditions. Surround suppression is also suggested by findings in several motion aftereffect (MAE) studies in which large, high-contrast OF-1 Supplier patterns produced attenuated MAEs (Falkenberg & Bex, 2007; Murakami & Shimojo, 1995; Sachtler & Zaidi, 1993; Tadin, Lappin, Gilroy, & Blake, 2003; Tadin, Paffen, Blake, & Lappin, 2008).
While the above-described results are consistent with suppressive center-surround mechanisms, further advancement in our understanding of surround suppression and its functional roles requires stronger linking of center-surround antagonism with its behavioral correlates. This raises the following question: what are the direct perceptual consequences of suppressive center-surround mechanisms? A simple prediction is that motion sensitivity should decrease with increasing stimulus size, but this prediction conflicts with established reports of strong spatial summation in motion (Anderson & Burr, 1991; Watson & Turano, 1995). Importantly, these psychophysical results relied on contrast thresholds measurements, which restricted their measurements to low-contrast stimuli. On the other hand, neurophysiological work on surround suppression was typically restricted to high-contrast motion stimuli. This stimulus difference is important because center-surround interactions can vary with contrast, with suppression dominating at high contrast and summation at low contrast (Nauhaus, Busse, Carandini, & Ringach, 2009; Sceniak, Ringach, Hawken, & Shapley, 1999).
Our results (Tadin et al., 2003) revealed that spatial integration of motion signals indeed critically depends on stimulus contrast (Fig. 1). At low-contrast, duration thresholds improved as stimulus size increased—replicating previous psychophysical results on spatial summation. At high-contrast, however, motion direction discriminations became substantially more difficult as the stimulus size increased. The observed effects were strong: the motion direction of large, high-contrast stimuli was several times less visible than the motion of the same stimuli when (1) shown at low-contrast, (2) embedded in dynamic noise (3) or presented at isoluminance. In order to clearly distinguish these psychophysical results from neurophysiological surround suppression, we use the term spatial suppression as referring to the psychophysical results indicating weakening of motion processing with increasing stimulus size. In a series of psychophysical studies, we and others have investigated spatial suppression using duration thresholds for motion direction discriminations (Betts, Sekuler, & Bennett, 2009; Betts, Taylor, Sekuler, & Bennett, 2005; Glasser & Tadin, 2010, 2011, 2014; Golomb et al., 2009; Lappin, Tadin, Nyquist, & Corn, 2009; Melnick, Harrison, Park, Bennetto, & Tadin, 2013; Tadin et al., 2003, 2006), MAE (Falkenberg & Bex, 2007; Tadin et al., 2003, 2008), reaction times (Tadin, Grdinovac, Hubert-Wallander, & Blake, 2007), binocular rivalry (Paffen, Alais, & Verstraten, 2005; Paffen, Tadin, te Pas, Blake, & Verstraten, 2006; Paffen, te Pas, Kanai, van der Smagt, & Verstraten, 2004) and reverse correlation (Neri & Levi, 2009; Tadin, Lappin, & Blake, 2006).

This study has certain limitations

This study has certain limitations that must be acknowledged. The sample size was small and the clinical observations were not blinded. We were unable to measure many additional cytokines and factors that could have potentially been involved. Therefore, further studies should include an assessment of alterations in the acute phase proteins such as C-reactive protein or late-phase alarmins, such as HMGB-1 (Wang et al., 1999; Yu et al., 2010a), etc. in the canine endotoxemia model treated with VPA.
Clinical improvements in anti-inflammatory effects such as blood pressure, platelet activation related to hemostasis (Yu et al., 2015), and serum biochemical analysis to evaluate organ injury after septic insult (Yu et al., 2012) should be evaluated in the future. The respiratory rate following VPA treatment should be further investigated since it could affect the oxygen content in the arterial blood.
The optimum concentration of VPA and the effective treatment time in the canine endotoxemia model remain unclear. We used a dose of 50mg/kg twice (12h interval) in this study whereas one dose of 100mg/kg has been used in other canine studies (Hu et al., 2011, 2012). We hypothesize that a more frequent drug administration for a longer period would yield better anti-inflammatory effects in a 24h model since VPA has a very short elimination Wnt agonist 1 in dogs (<3h) compared to humans (5–20h) (Plumb, 2011). A dosage of 100mg/kg instead of 50mg/kg may result in better immunologic and clinical outcomes. Thus, an additional study should be performed to determine the most effective dosage of VPA and to define suitable time points for administration.

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2057479).

Brucella are Gram-negative, facultative intracellular bacterial pathogens that may infect a range of different mammals including human, cattle, sheep, goat, swine, rodents and marine mammals (Cutler et al., 2005). Conventionally, the genus Brucella is classified into six classical species, based mainly on their preferred hosts and pathogenicity: B. melitensis, B. abortus, B. suis, B. canis, B. ovis and B. neotomae (Moreno et al., 2002; Pappas et al., 2005). Recently, four new Brucella species have been recognized and classified: B. pinnipedialis, B. ceti (Ross et al., 1996), B. microti (Scholz et al., 2008) and B. inopinata (Scholz et al., 2010).
Brucellosis, also known as “undulant fever”, “Mediterranean fever” or “Malta fever”, is a zoonosis primarily caused by infection with B. melitensis, B. abortus and/or B. suis. Human brucellosis is almost invariably transmitted by direct or indirect contact with Brucella-infected livestock or wildlife, consumption of milk or milk products, especially unpasteurized Wnt agonist 1 milk and cheese. Although considerable progress has been made in the control of this disease worldwide, brucellosis still frequently occurs in some countries or regions where the infection persists in domestic animals. Brucellosis remains an important infectious disease in many parts of the world, particularly in Asia, Sub-Saharan Africa, some countries in Latin America, the Middle East, the Mediterranean, and the South Eastern Europe Region (Nicoletti, 2010). Since 1995 the incidence of human brucellosis has sharply increased in China (Deqiu et al., 2002). Over 35,000 human cases were identified in 2010 by the laboratories of Chinese Center for Disease Control and Prevention (CDC) (Qiu et al., 2012), and about 85% cases were caused by B. melitensis infected sheep or goats (Deqiu et al., 2002; Zhang et al., 2010). Vaccination for animals is considered as the most efficient way to control brucellosis.
Vaccination has been suggested as the best strategy to prevent infections from intracellular bacterial pathogens. Hence, numerous Brucella vaccines have been developed and tested over the past several decades, but none is satisfactory and none has gained a wide acceptance. Currently, three live vaccines are commercially available: B. abortus S19, B. abortus RB51 and B. melitensis Rev 1 (Schurig et al., 2002). These live vaccines have been extensively used in the eradication of Brucellosis from livestock from the Western World. B. abortus RB51 is being used currently in many if not all western countries, which does not interfere with diagnosis. However, these live vaccine strains retain some virulence for humans and animals, especially young or pregnant ones, leaving a need to develop safer and more efficacious vaccines against Brucella infection (Alcantara et al., 2004; Kim et al., 2004; Yang et al., 2010). The bacterial-ghost technology may provide a novel alternative approach to develop such a vaccine.