There are described an image processing method, an image processing apparatus, an image processing program and an image recording apparatus characterized by reduced computation loads and capable of suppressing the mottled granular noise contained in color image signals and enhancing the sharpness of the image, without generating noises similar to color misregistration and false color contour appearing close to the edge. The image processing method includes the steps of: converting the image signals to luminance signals and chrominance signals; applying a Dyadic Wavelet transform processing to at least the luminance signals; suppressing a signal intensity of a high-frequency luminance component at P-th level, when the intensity of the high-frequency luminance component conforms to a specific condition; applying a Dyadic Wavelet inverse-transform processing to transformed and processed signals; and synthesizing processed luminance signals and the chrominance signals with each other to generate processed image signals.

The present invention relates to an image processing method, an image processing apparatus, an image processing program and an image recording apparatus; particularly to an image processing method, an image processing apparatus, an image processing program and an image recording apparatus for an image formed into image signals through scanning of a color photographic film.
The image formed on the color photographic film is optically read by a CCD sensor or the like and is converted into image signals. After having been subjected to various types of image processing represented by negative/positive reversal, brightness adjustment, color balance adjustment, removal of granular noise and enhancement of sharpness, such image signals are distributed through such media as a CD-R, floppy (R) disk and memory card or via the Internet, and are outputted as hard copy images on silver halide photographic paper by an inkjet printer, thermal printer or the like. Alternatively, such image signals are displayed on the medium such as CRT, liquid crystal display or plasma display to be viewed.
Generally, a photographic film image is formed by a collection of pigment clouds of various sizes. When this image is enlarged for observation, mottled granular irregularity is visible according to the size of pigment clouds, although uniform colors should appear. Corresponding granular noise signals are included in the image signals obtained by optical reading of the image formed on a photographic film, using a CCD sensor or others. These granular noise signals are increased considerably with image processing of sharpness enhancement in particular, with the result that image quality is deteriorated. This has created a problem.
In recent years, a less costly digital still camera (hereinafter abbreviated as "DSC") has come into widespread use. The DSC incorporated in such equipment as a cellular phone and laptop PC is also extensively used. The image sensor used in a less-costly DSC is characterized by a small pixel pitch. Shot noise tends to be produced at a low sensitivity, and not much consideration is given to cooling of an image sensor, so that conspicuous dark current noise is produced. The CMOS image sensor is often adopted in the less-costly DSC, so leakage current noise is conspicuous. When such noise is further subjected to image processing of interpolation of color filter arrangement and edge enhancement, the mottled granular irregularities are formed to deteriorate image quality. This has raised a problem. (For DSC noise and interpolation of color film arrangement, see the Non-Patent Document 1 listed later, for example).
To remove noise from image signals, the low-pass filter median filter technique is known. (See the Non-Patent Document 2 listed later, for example). However, noise removal by simple filtering involves reduced image sharpness, and a satisfactory image cannot be obtained.
Another widely known method for solving the above-mentioned problem is to use multiple filters to separate image signals into multiple frequency band components, and then to carry out suppression and enhancement for each frequency band. The Patent Documents 1 and 2 (listed later) propose the following technique, for example: Inputted image signals are decomposed into low, intermediate and high frequency band components, and enhancement processing is applied to the above-mentioned high frequency band components. At the same time, suppression processing is applied to the above-mentioned intermediate frequency band components. Processed high and intermediate frequency band components are synthesized with low frequency band components to get processed image signals, whereby granular noise is suppressed and sharpness is enhanced. By uniform suppression of the intermediate frequency band component where granular noise is mainly present, this technique has the effect of removing the granular irregularities that appear as mottles on the screen. However, since the information on image structure present on the intermediate frequency band components is also suppressed at the same time, shadow is suppressed on the bridge of the nose or around the eyes, for example, and the face appears blurred. A smooth expressionless face wearing makeup will appear.
The Patent Documents 3 and 4 (listed later) propose a technique of changing the filter conditions for each local site of an image, using the low-pass filter with varying sizes and shape. In this technique, the intermediate and high frequency band components are suppressed to remove the granular noise on the flat portion characterized by monotonous changes in brightness such as the cheek of the face or blue sky; whereas, on the edge portion such as hair and contour of the face characterized by sharp change in the brightness, a blur can be avoided without the intermediate frequency band components being suppressed. To get such an effect, however, a decision must be made to set the size and shape of the low-pass filter adequately for each step of processing. This takes much time and it is difficult to get sufficient effects by automatic processing of a desired image.
The frequency band is divided for each local site of an image, and a technique of using a wavelet transform is known as an effective way of suppression and enhancement for each frequency band. The details of wavelet transform are disclosed in the Non-Patent Documents 3 and 4. The following describes the overview:
The wavelet transform is operated as follows: In the first place, the following wavelet function is used, where vibration is observed in a finite range as shown in FIG. 1:
                                                        [                              Eq                .                                                                                1                            ]                                                                                ψ                                      a                    ,                    b                                                                                (                  x                  )                                            =                              ψ                                                                                (                                                            x                      -                      b                                        a                                    )                                                                                (        1        )
Using the above function, the wavelet transform coefficient <f, ψa, b>with respect to input signal f(x) is obtained by:
                                                        [                              Eq                .                                                                                2                            ]                                                                                〈                                  f                  ,                                      ψ                                          a                      ,                      b                                                                      〉                            ≡                                                1                  a                                                                  ∫                                                                                f                                                                          (                          x                          )                                                                    ·                                              ψ                                                                          (                                                                                x                              -                              b                                                        a                                                    )                                                                                ⅆ                      x                                                                                (        2        )
Through this process, input signal is converted into the sum total of the wavelet function.
                                                        [                              Eq                .                                                                                3                            ]                                                                                f                                                  (                  x                  )                                            =                                                ∑                                      a                    ,                    b                                                                                〈                                          f                      ,                                              ψ                                                  a                          ,                          b                                                                                〉                                    ·                                                            ψ                                              a                        ,                        b                                                                                (                      x                      )                                                                                (        3        )
In the above equation, "a" denotes the scale of the wavelet function, and "b" the position of the wavelet function. As shown in FIG. 1, as the value "a" is greater, the frequency of the wavelet function ψa, b(x) is smaller. The position where the wavelet function ψa, b(x) vibrates moves according to the value of position "b". Thus, Eq. 3 signifies that the input signal f(x) is decomposed into the sum total of the wavelet function ψa, b(x) having various scales and positions.
A great number of the wavelet functions are known, that allow the above-mentioned conversion. In the field of image processing, orthogonal wavelet and biorthogonal wavelet biorthogonal wavelet are put into common use. The following describes the overview of the conversion calculation of the orthogonal wavelet and biorthogonal wavelet.
Orthogonal wavelet and biorthogonal wavelet functions are defined as follows:
                                                        [                              Eq                .                                                                                3                            ]                                                                                ψ                                      i                    ,                    j                                                                                (                  x                  )                                            =                                                2                                      -                    i                                                                                ψ                                                        (                                                                  x                        -                                                  j                          ·                                                      2                                                                                i                                                                                2                                                                                i                                                              )                                                                                (        4        )
where "i" denotes a natural number.
Comparison between Eq. 4 and Eq. 1 shows that the value of scale "a" is defined discretely by an i-th power of "2", according to orthogonal wavelet and biorthogonal wavelet. This value "i" is called a level. In practical terms, level "i" is restricted up to finite upper limit N, and input signal is converted as follows:
                                                        [                              Eq                .                                                                                5                            ]                                                                                f                                                                          (                          x                          )                                                                    ≡                                                                                S                        0                                                              =                                                                                ∑                          j                                                                                〈                                                                                S                                0                                                            ,                                                              ψ                                                                  1                                  ,                                  j                                                                                〉                                                    ·                                                                                ψ                                                              1                                ,                                j                                                                                (                              x                              )                                                                                +                                                                        ∑                          j                                                                                〈                                                                                S                                0                                                            ,                                                              ψ                                                                  1                                  ,                                  j                                                                                〉                                                    ·                                                                                ϕ                                                              1                                ,                                j                                                                                (                              x                              )                                                                                ≡                                                                                ∑                          j                                                                                W                              1                                                                                (                              j                              )                                                                                ·                                                                                ψ                                                              1                                ,                                j                                                                                (                              x                              )                                                                                +                                                                        ∑                          j                                                                                S                              1                                                                                (                              j                              )                                                                                ·                                                                                ϕ                                                              1                                ,                                j                                                                                (                              x                              )                                                                                (        5        )                                                                                S                                  i                  -                  1                                            =                                                                                ∑                    j                                                                                〈                                                                        S                                                      i                            -                            1                                                                          ,                                                  ψ                                                      1                            ,                            j                                                                                〉                                        ·                                                                  ψ                                                  1                          ,                          j                                                                                (                        x                        )                                                                                +                                                      ∑                    j                                                                                〈                                                                        S                                                      i                            -                            1                                                                          ,                                                  ψ                                                      1                            ,                            j                                                                                〉                                        ·                                                                  ϕ                                                  1                          ,                          j                                                                                (                        x                        )                                                                                ≡                                                                                ∑                    j                                                                                W                        1                                                                                (                        j                        )                                                              ·                                                                  ψ                                                  1                          ,                          j                                                                                (                        x                        )                                                                                +                                                      ∑                    j                                                                                S                        1                                                                                (                        j                        )                                                              ·                                                                  ϕ                                                  1                          ,                          j                                                                                (                        x                        )                                                                                (        6        )                                                      f                                      (              x              )                                ≡                                          S            0                          =                                            ∑                              i                =                1                            N                                                                  ∑                j                                                                                W                    i                                                                          (                    j                    )                                                  ·                                                      ψ                                          1                      ,                      j                                                                                (                    x                    )                                                                                +                                    ∑              j                                                                                S                  N                                                                  (                  j                  )                                            ·                                                ϕ                                      1                    ,                    j                                                                                (                  x                  )                                                                                (        7        )
The second term of Ex. 5 denotes that the low frequency band component of the residue that cannot be represented by the sum total of wavelet function ψ1, j(x) of level 1 is represented in terms of the sum total of scaling function φ1, j(x). An adequate scaling function in response to the wavelet function is employed (See Non-patent Documents 3 and 4 listed later). This means that input signal f(x)≡S0 is decomposed into the high frequency band component W1 and low frequency band component Si of level 1 by the wavelet transform of level 1 shown in Eq. 5. Since the wavelet function ψi, j(x) of the minimum traveling unit of the wavelet function ψi, j(x) is 2i, each of the signal volume of high frequency band component W1 and low frequency band component S1 with respect to the signal volume of input signal "S0" is ½. The sum total of the signal volumes W1 and S1 is equal to the signal volume of input signal "S0". The low frequency band component S1 of level 1 is decomposed into high frequency band component W2 and low frequency band component S2 of level 2 by Eq. 6. After that, transform is repeated up to level N, whereby input signal "S0" is decomposed into the sum total of the high frequency band components of levels 1 through N and the sum of the low frequency band components of level N, as shown in FIG. 7.
Here the wavelet transform of level 1 shown in Eq. 6 is known to be computed by filtering, as shown in FIG. 2 (See Non-Patent Documents 3 and 4). In FIG. 2, LPF denotes a low-pass filter and HPF a high-pass filter. An appropriate filter coefficient is determined in response to the wavelet function (See Non-Patent Documents 3 and 4). Symbol 2↓ shows the down sampling where every other samples are removed (thinned out). The wavelet transform of level 1 in the secondary signal such as image signal is computed by the processing of filtering as shown in FIG. 3. In FIG. 3, LPFx, HPFx and 2↓x denote processing in the direction of "x", whereas LPFy, HPFy and 2↓y denote processing in the direction of "y". The low frequency band component Sn−1 is decomposed into three high frequency band components Wvn, Whn, Wdn and one low frequency band component Sn by the wavelet transform of level 1. Each of the signal volumes of Wvn, Whn, Wdn and Sn generated by decomposition is ½ that of the Sn−1 prior to decomposition in both vertical and horizontal directions. The total sum of signal volumes of four components subsequent to decomposition is equal to the signal Sn−1 prior to decomposition. FIG. 4 is a schematic diagram representing the process of the Input signal S0 being decomposed by the wavelet transform of level 3.
Further, when wavelet inverse transform is applied to Wvn, Whn, Wdn and Sn generated by decomposition, the signal Sn−1 prior to decomposition is known to be re-configured completely. In FIG. 5, LPF′ denotes a low-pass filter and HPF′ a high-pass filter. In the case of orthogonal wavelet, the same coefficient as that used in the wavelet transform is used as this filter coefficient; whereas in the case of biorthogonal wavelet, the coefficient different from that used in the wavelet transform is used as this filter coefficient. (See the above-mentioned Reference Documents). Further, 2↑ denotes the up-sampling where zero is inserted into every other signals. The LPF′x, HPF′x and 2↑x denote processing in the direction of "x", whereas LPF′y, HPF′y and 2↓y denote processing in the direction of "y".
The following image processing method is proposed as a known technique: Image signals are decomposed into multiple frequency band components by such a orthogonal wavelet and a biorthogonal wavelet, and each frequency band components is edited (data-processed). After that, inverse-transform is applied to configure image signals with reduced noise. According to Patent Document 5, the image signal representing the radiation screen is subjected to wavelet transform, whereby the above-mentioned image signals are decomposed into multiple frequency band components. The specified frequency band component out of the above-mentioned multiple frequency band components is subjected to the processing wherein signal values where the absolute value of each of the above-mentioned signal value is below the specified threshold value is reduced to 0. When inverse wavelet transform is applied to the frequency band component subjected to the above-mentioned processing and other frequency band components, image signals with reduced noise are obtained. In this image processing method, however, when the above-mentioned is applied to color images, the RGB balance close to the edge of the subject is lost, and a false color contour appears. This is very unseemly. In the noise structure of image signals gained by optical reading of the image formed on the color photographic film with a CCD sensor, mottled granular irregularities based on the size of the coloring pigment cloud is predominant, unlike the radiation image. If such a big threshold value as to erase this mottled irregularities is set, the sharpness of the image will be lost, or an artifice will appear. Conversely, when the threshold value is S0 small that the sharpness of the image is maintained, the mottled irregularities will not be erased. For these reasons, application of the technology of Patent Document 5 to a color image does not ensure satisfactory effects.
According to Tokkai 2000-224421, wavelet transform is applied to image signals to decompose the above-mentioned image signals into multiple frequency band components. Noise extraction processing is applied to the specified frequency band components, and noise elimination processing is applied to the above-mentioned specified frequency band components, based on the result of above-mentioned extraction processing, whereby processed frequency band components are obtained. Wavelet transform processing is applied to the above-mentioned processed frequency band components to get the low frequency band component one-step lower (of higher level) than the above-mentioned specified frequency band components. Processed frequency band component is obtained for each frequency band component by repeating the above-mentioned extraction processing wherein the above-mentioned low frequency band component one-step lower is the above-mentioned specified frequency band component, the above-mentioned noise elimination processing and the above-mentioned wavelet transform processing, until a desired frequency band is reached. Image signals with reduced noise are obtained by applying inverse wavelet transform to the above-mentioned processed frequency band component. However, when the above-mentioned technology is applied to color images, RGB balance is lost in the area where mottled irregularities are erased, with the result that false color spots appear. This is very unseemly. Further, noise extraction of low frequency signals and noise elimination processing must be repeated for each one-level transform, imposing a heavy computational load. Further, the medical image assumed in Patent Document 6 is restricted in the type of a subject, and comparatively monotonous images often occur. By contrast, the color photographic image is characterized by the mixed areas of different picture quality—an area where fine structures are closely packed in an image, the flat area, a bright area and a dark area, as in a people portrait against the background of a forest. In such a color image, noise elimination conditions must be changed, based on the area structure captured in perspective. According to the method given in the Patent Document 6, the noise elimination processing condition on the resolution level "n" must be determined according to the information on the above-mentioned resolution of level "n". This makes it difficult to design an algorithm for determining the noise elimination conditions.
Non-Patent Documents 5, 6 and 7 give a detailed explanation to the Dyadic Wavelet used in the present invention. The following gives the overview:
The wavelet function of the Dyadic Wavelet is defined as follows:
                                                        [                              Eq                .                                                                                6                            ]                                                                                ψ                                      i                    ,                    j                                                                                (                  x                  )                                            =                                                2                                      -                    i                                                                                ψ                                                        (                                                                  x                        -                        j                                                                    2                                                                                i                                                                                )                                                                                (        8        )
where "i" denotes a natural number.
Wavelet functions of orthogonal wavelet and biorthogonal wavelet are discretely defined when the minimum traveling unit of the position on level "i" is 2i, as described above. By contrast, in the two-term wavelet, the minimum traveling unit of the position is constant, despite level "i". This difference provides the Dyadic Wavelet transform with the following characteristics:
Characteristic 1: The signal volume of each of high frequency band component Wi and low frequency band component Si generated by the Dyadic Wavelet transform is the same as that of signal Si−1 prior to transform.
                                                        [                              Eq                .                                                                                7                            ]                                                                                S                                              i                        -                        1                                                              =                                                                                ∑                          j                                                                                〈                                                                                S                                                                  i                                  -                                  1                                                                                ,                                                              ψ                                                                  i                                  ,                                  j                                                                                〉                                                    ·                                                                                ψ                                                              i                                ,                                j                                                                                (                              x                              )                                                                                +                                                                        ∑                          j                                                                                〈                                                                                S                                                                  i                                  -                                  1                                                                                ,                                                              ϕ                                                                  i                                  ,                                  j                                                                                〉                                                    ·                                                                                ϕ                                                              i                                ,                                j                                                                                (                              x                              )                                                                                ≡                                                                                ∑                          j                                                                                W                              i                                                                                (                              j                              )                                                                                ·                                                                                ψ                                                              i                                ,                                j                                                                                (                              x                              )                                                                                +                                                                        ∑                          j                                                                                S                              i                                                                                (                              j                              )                                                                                ·                                                                                ϕ                                                              i                                ,                                j                                                                                (                              x                              )                                                                                (        9        )
Characteristic 2: The following relationship is found between the scaling function φi, j(x) and wavelet function ψi, j(x):
                                                        [                              Eq                .                                                                                8                            ]                                                                                ψ                                      i                    ,                    j                                                                                (                  x                  )                                            =                                                                    ∂                                                                                ∂                    x                                                                                ϕ                                          i                      ,                      j                                                                                (                    x                    )                                                                                (        10        )
Thus, the high frequency band component Wi generated by the Dyadic Wavelet transform represents the first differential (gradient) of the low frequency band component Si.
Characteristic 3: With respect to Wi·γi (hereinafter referred to as "compensated high frequency band component) obtained by multiplying the coefficient γi (see the above-mentioned Reference Document on Dyadic Wavelet)) determined in response to the level "i" of the Wavelet transform, by high frequency band component, the relationship between levels of the signal intensities of compensated high frequency band components Wi·γi subsequent to the above-mentioned transform obeys a certain rule, in response to the singularity of the changes of input signals. To put it another way, the signal intensity of the compensated high frequency band component Wi·γi corresponding to smooth (differentiatable) signal changes shown by 1 and 4 of FIG. 6 increases with level number "i"; whereas the signal intensity of the compensated high frequency band component Wi·γi corresponding to stepwise signal changes shown by 2 of FIG. 6 stays constant independently of the level number "i", and the signal intensity of the compensated high frequency band component Wi·γi corresponding to functional signal changes shown by 3 of FIG. 6 decreases with increase in level number "i".
Characteristic 4: Unlike the above-mentioned method of orthogonal wavelet and biorthogonal wavelet, the method of Dyadic Wavelet transform on level 1 in the 2-D signals such as image signals is followed as shown in FIG. 7. The low frequency band component Sn−1 is decomposed into two high frequency band components Wxn, Wyn and one low frequency band component Sn by the wavelet transform of level 1. Two high frequency band components correspond to components x and y of the change vector Vn in the two dimensions of the low frequency band component Sn. The magnitude Mn of the change vector Vn and angle of deflection An are given by the following equation:
[Eq. 9]Mn=√{square root over (Wxn2+Wyn2)}  (11)An=argument (Wxn+iWyn)  (12)
It has been known that Sn−1 prior to transform can be re-configured when the Dyadic Wavelet inverse transform shown in FIG. 8 is applied to two high frequency band components Wxn, Wyn and one low frequency band component Sn.
In Patent Document 5, the following method is proposed to eliminate the white noise (Gaussian white noise) superimposed onto the monochrome image using the Dyadic Wavelet.
Step 1: The maximum of high frequency band component on each level is sought, and correspondence of the maximum positions between levels is established.
Step 2: When the absolute values of the associated maxima are reduced with increase in the level number, the maxima are removed.
Step 3: The linkage of remaining maxima on the plane surface is checked, and those having the linkage length in excess of the threshold value are preserved without being removed.
In addition to the above procedures, the following operations are also expounded:
Step 4: All signal values of the high frequency band component on the first level are discarded and signal values are synthesized according to the following method:                <1> The position of the maximum is made the same as that of the maximum on the second level left behind subsequent to the operations of steps 1 through 3.        <2> The magnitude M1 of the first level is determined by extrapolation of intensity between the levels higher than the second level of the magnitude Mn of the change vector defined in Eq. 11 in the above-mentioned position.        <3> The value A2 on the second level of the deflection angle An of the change vector defined in Eq. 12 in the above-mentioned position is copied to deflection angle A1 on the first level.        <4> The signal value of the high frequency band component on the first level is synthesized from the M1 and A1 obtained above.
The method proposed above requires a great amount of computation, and much time and labor. Further, noise superimposed on image signals is assumed as white noise. S0 if this method is applied to the image containing mottled granular noise, as found in the case of the image gained by scanning a silver halide film or less costly DSC image, granular noise elimination will be insufficient or part of the granular noise will be enhanced. Further, if the above-mentioned method is applied to each of the RGB planes of a color image, a new fine granular noise similar to color misregistration will appear, raising another problem.
The documents cited in the above descriptions are listed as follow:
Patent Document 1: Tokkaihei 9-22460Patent Document 2: Tokkai 2000-215307Patent Document 3: Tokkai 2001-143068Patent Document 4: Tokkai 2001-155148Patent Document 5: Tokkaihei 9-212623Patent Document 6: Tokkai 2000-224421
Non-Patent Document 1: "Digital Photography" Chapter 2 and 3, published by The Society of Photographic Science and Technology of Japan, Corona Publishing Co., Ltd.
Non-Patent Document 2: "Practical Image Processing learnt in C-language" P54, by Inoue et al., Ohm Publishing Co., Ltd.
Non-Patent Document 3: "Wavelet and Filter Banks" by G. Strang & T. Nguyen, Wellesley-Cambridge Press
Non-Patent Document 4: "A wavelet tour of signal processing 2ed." by S. Mallat, Academic Press
Non-Patent Document 5: "Singularity detection and processing with wavelets" by S. Mallat and W. L. Hwang, IEEE Trans. Inform. Theory 38 617 (1992)
Non-Patent Document 6: "Characterization of signal from multiscale edges" by S. Mallet and S. Zhong, IEEE Trans. Pattern Anal. Machine Intel. 14 710 (1992)
Non-Patent Document 7: "A wavelet tour of signal processing 2ed." by S. Mallat, Academic Press

Image processing method, image processing apparatus, image processing program and image recording apparatus


A new and distinct cultivar of Petunia plant named ‘Fort Trailing Light Lavender’, characterized by its outwardly spreading to trailing growth habit; freely branching habit; freely flowering habit; large lavender-colored flowers; and good garden performance.

The present invention relates to a new and distinct cultivar of Petunia, botanically known as Petunia×hybrida and hereinafter referred to by the name 'Fort Trailing Light Lavender'.
The new Petunia is a product of a planned breeding program conducted by the Inventor in De Lier, The Netherlands. The objective of the breeding program is to create new freely-branching Petunia cultivars with early and freely flowering habit, and unique and attractive flower color.
The new Petunia originated from a cross-pollination made by the Inventor in 1999 in De Lier, The Netherlands of two unnamed proprietary selections of Petunia×hybrida, not patented. The new Petunia was discovered and selected by the Inventor as a single flowering plant within the progeny of the stated cross-pollination in a controlled environment in De Lier, The Netherlands.
Asexual reproduction of the new Petunia by terminal cuttings in a controlled environment in De Lier, The Netherlands since 2003, has shown that the unique features of this new Petunia are stable and reproduced true to type in successive generations.


Various embodiments may relate to a lighting module, including a first printed circuit board, on which at least one light source is arranged, a covering element, which at least partially covers the first printed circuit board, and at least one electronic component, which is integrated in the covering element and is electrically connected to the first printed circuit board.

Lighting modules usually include a printed circuit board with one or more light sources arranged on the upper side thereof, and a covering element, which at least partially covers the printed circuit board. In addition, provision is generally made for the lighting modules to have an external driver or control gear, in which one or more electronic components which are required for operating the light sources on the printed circuit board are arranged. These one or more electronic components are connected to the printed circuit board having one or more light sources. A large amount of installation space is required for the lighting module, in particular in a lighting device, owing to such an external driver or such external control gear.


An implant release mechanism for releasing, for example, a stent (60) is provided with three restraining wires (62) which pass in the space between a wire guide catheter (24) and a pusher sheath or dilator (30) and are arranged substantially equi-angularly threrearound. Each restraining wire (62) holds both the proximal and distal ends of the stent (60), in this case each holding a proportion of the ends of the stent (60). When the restraining wires (62) are pulled they will first unwrap from the proximal end of the stent (60) and will then release the distal end of the stent (60) so as to allow the stent to become fully deployed within the lumen of the patient. The use of common release wires improves deployment of implants and reduces the number and volume of components in the device, thereby allowing it to occupy a smaller volume.

When an expandable endovascular prosthesis or implant, such as a stent, is deployed, it is very important to position it at the precise desired location within the patient's lumen. With some prior art stent delivery systems, as soon as the covering sheath is withdrawn to expose the underlying stent, the distal end of the stent expands in a rapid and irregular way, with the risk that one or more of the struts of the stent is deformed irregularly, such as being bent backwards. The risk of such an occurrence is increased in cases where the distal end of the delivery device on which the stent is located is not in the middle of the vessel.
Moreover, in the final stages of deployment, when the sheath slides over and beyond the distal end of the stent, this will expand in a manner which is difficult to control. This lack of control makes the placement of the implant less accurate and can also lead to damage to the intima of the vessel.
These problems tend to be exacerbated in the deployment of dissection stents for treating aortic dissections. The reason is that dissection stents tend to be very pliable and therefore require careful deployment in order not to be twisted, damaged or otherwise compromised.
In order to mitigate the problems described above, it is known to restrain the ends of the implant so as to keep it in a substantially compressed form on withdrawal of the sheath. The ends are then released to complete the deployment of the device. For example, in the case of a stent or stent-graft, the ends thereof are held tightly against the deployment catheter until released by the clinician. For this purpose, there are provided release devices at both the distal and the proximal ends of the stent or stent-graft. It is known to use release wires for the release devices, which release wires tie the ends of the stent or stent-graft until release is effected.
For example, US-2006/0,142,836 discloses a delivery device in which the proximal end of the stent graft is held by a plurality of restraining wires coupled through sutures to the apices of the proximal-most hoop of the stent. If desired, the distal end of the stent could be likewise secured by a plurality of distal end restraining wires. In order to release the stent-graft, the sheath is removed, then the proximal and distal ends released, as determined by the surgeon after final alignment of the stent-graft in the patient's lumen, by manipulation of a release mechanism which loosens the restraining wires.
US-2004/0,073,289 discloses a delivery system which is provided with a series of restraining wires for holding the proximal end of the stent-graft and a distal collar for restraining the distal end of the stent-graft. The two release mechanisms are deployable separately to release the proximal and distal ends of the stent-graft as required by the particular medical procedure.
These prior art systems can mitigate the problems described above. However, they can be difficult for a surgeon to deploy by requiring the provision of different release mechanisms at the proximal or external manipulation end of the deployment device.
In the case of certain types of implant, such as dissection stents, the deployment of the stent involves particular difficulties in light of the delicate nature of the stent, that is because of its extreme flexibility. It has been known for such a stent to become twisted as a result of rotation of the delivery device during the deployment operation, caused by having to deploy different release mechanisms and at different times.
Another problem with these prior art systems is that they necessarily take up a certain volume within the delivery device, which limits the minimum achievable diameter of the delivery device.


A method for aiding in the determination of whether a living or deceased human is afflicted with or will likely have atherosclerosis respectfully, the method comprising determining the level of SPRR3 protein in a intimae or body fluid sample by using molecular localization analysis technique comparing the determined level of SPRR3 protein in the biological sample obtained from said individual with a range of SPRR3 levels previously defined as characteristic for humans having atherosclerosis, concluding from the comparison that the person is likely suffering from atherosclerosis when a SPRR3 level is in the range previously defined as characteristic for the presence of atherosclerosis as an indication that the individual is suffering from or has suffered from atherosclerosis.

Coronary heart disease (CHD) is the leading cause of death in humans in the U.S. CHD is so pervasive that more humans die of CHD than from any other disease. CHD is caused by a narrowing of the coronary arteries that supply blood to the heart. Too often, this narrowing tragically results in a heart attack in the victim. Unfortunately, each year about a million Americans have a heart attack and tragically about half or more of these heart attacks are fatal even before the heart attack victim can get to a treatment facility.
Without being bound by theory, in one aspect of early stage of CHD (atherosclerosis), it is believed that plaque or fatty materials build up inside the walls of human arteries (carrying oxygenated blood) along with blood components which are attracted to the plaque or fatty materials and sometimes an atheroma results. Sometimes the fatty buildup or plaque breaks open (i.e. plaque rupture) in a human artery which leads to formation of a clot that seals a defect in the artery but unfortunately restricts blood flow resulting in an acute vascular event. When too little blood reaches the beating heart as a result of this restriction in blood flow, ischemia results.
When ischemia is of a long duration there is generally a resulting heart attack which unfortunately is all too often sometimes fatal. In some situations ischemia disturbs the heart's normal rhythm inducing an abnormal increasingly disruptive rhythm such as malignant ventricular arrhythmia which is also usually destructively fatal. Overall, it is the progressive stenosis of an arterial lumen that is believed to be a major contributing factor to a fatal heart attack results for the victim.
In an effort to combat human heart attacks, medical research strives to identify those individuals pre-attack with a high risk toward atherosclerosis and to identify a preventative or treatment regime for them such as an alternative lifestyle, and to identify drugs which are effective against arterial atherosclerosis.
Difficult challenges are presented in that the process of discovering and developing new pharmaceutical drugs is increasingly expensive and challenging. For example, the average length of time from the discovery of a candidate drug to the time of its U.S. Federal Drug Administration approval has increased. And currently it is estimated that an average of 10,000 or more lead (candidate) compounds must be tested in pre-clinical development for every drug that is finally marketed.
Additionally it is estimated that existing pharmaceutical drugs interact with less than five hundred or so biological targets out of an estimated large number of potential targets (˜10,000). If this estimate is correct then, this means that the majority of potential drug targets remain undiscovered using presently available techniques.
Thus, despite rapid and noteworthy advances in medical science in this field, a dire need exists for accurately determining the risk to atherosclerosis to individuals, for alerting such individuals to their existing or developing risk, for providing a treatment regime to an afflicted human and for a method of identifying pharmacological drugs which are therapeutic to preventing or ameliorating dangerous and potentially fatal CHD. Further, it is highly desired to have a sensitive and specific biomarker to assess the extent of atherosclerosis in human arteries.

Method of assessing the risk of atherosclerosis


In view of the increase in the number of cases with nephropathy in aged animals of the cat family, the invention provides a marker for early diagnosis of feline nephropathy which can substitute for the conventional complicated methods of diagnosing nephropathy such as blood examination, kidney radiography using a contrast medium, and ultrasonic image analysis. It was found that cats with nephropathy show markedly lowered levels of excretion of a novel protein (named cauxin) with a molecular weight of 70 K, which is excreted into urine in high concentrations in normal adult cats showing no clinical abnormality. When the protein is used as a marker in diagnosing feline nephropathy, feline nephropathy can be detected in a simple and exact manner.

Under considerable daily stresses of life in these days, those individuals who wish to live with a pet are increasing in number, and the number of pet dogs and cats is increasing year after year. On the other hand, with the advancement in veterinary medicine and popularization of pet foods, the number of dogs and cats of advanced age is increasing and, like in humans, the incidence of adult diseases, obesity and nephropathy (renal diseases), among others, is increasing, raising a serious problem. As regards nephropathy, in particular, it is very difficult to recognize a disease signal at an early stage, as suggested by the saying that the kidney is a silent organ. Therefore, upon veterinary examination in view of some or other symptoms, the renal function is found to be in severe disorder in many instances.
In clinical veterinary medicine, the cases of renal diseases have been increasing in recent years with the aging of animals of the family Felidae and, at present, nephropathy is the primary cause of death among family cats. Further, the symptoms of nephropathy are noticed in most cases only when they are already in advanced stages and, thus, the disease is often already in an incurable stage at the time of consultation with a veterinarian. Thus, chronic renal failure is ranked high in the list of causes of deaths of cats.
The clinical symptoms of nephropathy, in particular chronic renal failure, are such general or constitutional symptoms as polyposia and polyuria, anorexia, weight loss, vomiting, diarrhea, dehydration, anemia, and depression. Diagnosis is carried out by or according to an interview with the owner, urinalysis, blood examination, renal biopsy, and imaging, among others. As general indicators of nephropathy, there may be mentioned blood urea nitrogen (hereinafter, BUN), serum creatinin (hereinafter, CRE), and proteinuria. However, accelerative increases in both BUN and CRE are observed only after a decrease in glomerular filtration value (an index in renal function evaluation) to 25% of the normal level or below, hence they cannot serve as markers for early diagnosis. In addition, the BUN is influenced by meals, and the CRE by physical activity. As for the urinary protein, or proteinuria, it is one of findings suggesting disorders of kidneys and is so important that when it is found, nephropathy is suspected first of all. However, while the protein excretion in normal human urine is 3 mg or less/kg/day, the protein excretion in feline urine is as high in concentration as 17.43±9.03 mg/kg/day even in normal conditions. Thus, the equation proteinuria=nephropathy can hardly be formulated.
Under such circumstances, the advent of a marker for early diagnosis of feline nephropathy is now earnestly desired.
The conventional methods of diagnosing nephropathy mainly utilize such complicated techniques as blood examination, radiography of kidneys using a contrast medium, ultrasonic image analysis, and so forth. It is demanded that a more easy and simple method be developed. Further, it is desired that a method by which the owner can check the health status of a cat in a simple and easy manner without visiting a veterinarian and a test kit therefor be developed. A convenient test reagent is also required with which feline nephropathy can easily be found before the disease becomes incurable, with the result that the life of a family cat can be prolonged.


Receiver circuits in serial lanes each generate a synchronous clock signal that is aligned with a master clock signal to allow synchronous transfer of data onto the master clock domain without corruption. A serial-to-parallel converter circuit in each receiver circuit converts a serial data signal into parallel data signals in response to one of the synchronous clock signals. Phase detection circuitry generates an indication of a phase shift based on a phase offset between the synchronous and master clock signals. A clock signal generation circuit provides an adjustment to a phase of the synchronous clock signal based on the indication of the phase shift. The serial-to-parallel converter circuit adjusts positions of bits indicated by the parallel data signals based on the adjustment to the phase of the synchronous clock signal.

Data is often transmitted in serial at a high data rate between integrated circuits. When more bandwidth is required than the desired serial data rate, data is spread across multiple serial data streams through distribution, carried across a given medium, and aggregated at the receiving end. Each serial data stream transmitted across the medium may experience a different propagation delay, causing each serial data stream to lose its associated alignment with the other serial data streams forming the link.
An integrated circuit receives a serial data signal from another integrated circuit. The receiving integrated circuit can convert the serial data in the serial data signal into parallel data to allow for operation of digital logic at lower speeds. For example, the receiving integrated circuit may convert the incoming serial data signal into successive bytes or words of parallel data. The parallel data has a lower data rate than the serial data. The parallel data is stored in the receiving integrated circuit at a lower clock frequency than the clock frequency used to sample the serial data.

Techniques for alignment of parallel signals


A piezoelectrically actuated element includes a composite ceramic to which an alternating electric field is applied through external electrodes that are orthogonal to the polarization direction, wherein the composite ceramic is formed from a first piezoelectric ceramic having soft spring characteristics such that the elastic constant decreases with increasing vibration velocity, and a second piezoelectric ceramic having hard spring characteristics such that the elastic constant increases with increasing vibration velocity. Even when the applied electric field is intensified to increase the vibration velocity of the piezoelectrically actuated element, the overall change in the elastic constant is minimized, and fluctuations in the resonance frequency is suppressed.

Resonant actuators having the constitution shown in FIG. 7 (A) have been known. The resonant actuator 200 shown in FIG. 7 (A) is constituted by a piezoelectric ceramic material 202 formed in the shape of a square bar, with electrodes 204a, 204b provided on both end faces of the material. The resonant actuator 200 is polarized in the direction of arrow a and constituted in such a way that an AC electric field is applied to the electrodes 204a, 204b to drive the actuator at and near a resonance frequency so as to obtain vertical vibration in the direction of arrow b which is the same as the polarization direction a. Normally an AC electric field is applied to the electrodes 204a, 204b by connecting conductive wires 208a, 208b connected to an AC power supply, to the electrodes 204a, 204b, via spring terminals 206a, 206b, or by directly connecting the electrodes 204a, 204b to the conductive wires 208a, 208b.
Also, International Patent Laid-open No. 2008/090758 (Patent Literature 1) proposes the constitution shown in FIG. 7 (B) by considering possible inhibition, by the spring terminals 206a, 206b and conductive wires 208a, 208b, of the vibration of the resonant actuator 200. The constitution of the resonant actuator 250 shown in FIG. 7 (B) is to suppress inhibition of vibration by using lead conductors 258a, 258b to lead out electrodes 254a, 254b, provided on both end faces of a piezoelectric ceramic material 252 of square bar shape, to the centers of the side faces of the piezoelectric ceramic material 252, while pressing connection electrodes 256a, 256b using spring terminals 260a, 260b.
This type of resonant actuator is considered to be normally displaced, in the vibration direction, by an amount proportional to the piezoelectric constant d. In the field of ceramic materials for resonant actuators, therefore, active research and development efforts have been underway to obtain piezoelectric materials based on Pb(Zr,Ti)O3 (lead zirconate titanate (hereinafter referred to as "PZT")) having a high piezoelectric constant. For example, "Atsuden Zairyo no Shin Tenkai (New Development of Piezoelectric Materials)" by Sadayuki Takahashi, TIC Co., Ltd., New Ceramics Vol. 11, No. 8 (1998), pp. 29-34 (Non-patent Literature 1) describes the large amplitude characteristics of piezoelectric ceramics used for piezoelectric actuators and other power devices, utilizing the large amplitude elastic vibration of piezoelectric ceramics. Non-patent Literature 1 reports that, while theoretically the vibration speed (=vibration amplitude×frequency) changes in proportion to the applied electric field E, driving PZT piezoelectric ceramics at a resonance frequency will cause the vibration speed to gradually drop to and eventually below the theoretical value once the electric field intensity exceeds a certain level.
Also, "Haipawaa Zairyo no Hyoka (Evaluation of High-power Materials)" by Sadayuki
Takahashi, TIC Co., Ltd., New Ceramics (1995), No. 6, pp. 17-21 (Non-patent Literature 2) reports that driving PZT piezoelectric ceramics at a resonance frequency will cause the resonance frequency fr and mechanical quality coefficient to drop once the vibration level exceeds a certain value. In addition, it is known that a resonant actuator using conventional PZT piezoelectric ceramics will see its resonance frequency and mechanical quality coefficient drop as the vibration speed rises. When AC voltages of 0.05 V, 0.11 V, 0.14 V, 0.20 V, 0.26 V and 0.33 V were actually applied to a resonant actuator of a PZT piezoelectric ceramic and the drive frequency was swept from above to below, and from below to above, a resonance frequency, the resonance frequency representing the maximum vibration speed was moved to a low frequency side as the amplitude of the AC electric field increased, as shown in FIG. 7 (C). The vibration speed did not return even when the frequency was lowered, and a hysteresis was observed.
This suggests a need for a feedback circuit to follow changes in the resonance frequency fr. In the field of piezoelectric actuators, etc., where high-power materials of high vibration levels are required, evaluation methods for piezoelectric property as well as relationships of compositions of PZT piezoelectric ceramics on one hand, and vibration level characteristics and other high-power characteristics on the other, are reported. To solve this problem, International Patent Laid-open No. 2007/083475 (Patent Literature 2) reports a resonant actuator constituted by a ceramic offering high mechanical quality coefficient, being highly temperature stable, and containing an oriented bismuth layered compound, by arguing the relationship of "Vibration speed α (Elastic constant)½×Piezoelectric constant×Mechanical quality coefficient×Electric field."

Piezoelectric drive element and piezoelectric drive unit


An apparatus generally having a plurality of disk drives and a controller is disclosed. Each of the disk drives may have a first region and a second region. The first regions may have a performance parameter faster than the second regions. The controller may be configured to (i) write a plurality of data items in the first regions and (ii) write a plurality of fault tolerance items for the data items in the second regions.

Circular disk media devices rotate at a constant angular velocity while accessing the media. Therefore, a read/write rate to and from the media depends on the particular track being accessing. Access rates conventionally increase as distance increases from a center of rotation for the media. Referring to FIG. 1, a block diagram illustrating a conventional mapping for a redundant array of inexpensive disks (RAID) level 1 system is shown. The RAID 1 system is commonly viewed by software as a virtual disk 10 having multiple contiguous logical block addresses (LBA). Each virtual LBA may be stored on a data drive 12 at a physical LBA. Each physical LBA may also be mirrored to and stored in a parity drive 14. Therefore, each virtual LBA is stored at the same physical LBA location in both the data drive 12 and the parity drive 14.
The RAID 1 system can be implemented with more than two disk drives. An equal number of data drives 12 and parity drives 14 will exist for the RAID 1 virtual disk 10 with each of the parity drives 14 containing a mirror image of a data drive 12. Furthermore, access time to the virtual disk 10 will increase as a position of the LBA number moves closer (i.e., increases) to the axis of rotation for the disk drive media. In the LBA mapping scheme illustrated, a random read performance of the RAID 1 virtual disk 10 matches that of either single disk 12 or 14.


The present invention provides stabilized prolonged release pharmaceutical compositions comprising atypical antipsychotic drug like paliperidone or pharmaceutically acceptable salts thereof without incorporating surfactant and/or water penetration enhancer. Such compositions are preferably in the form of a matrix wherein one or more release controlling agents are present in and/or on the matrix. Further, such compositions comprise one or more release controlling agent and exhibits desired in vitro release of drug with or without lag period. The invention also provides a process for the preparation of such compositions.

Paliperidone is an atypical antipsychotic drug, also known as second generation antipsychotic drug and is described in U.S. Pat. No. 4,804,663. It is practically insoluble in water, and sparingly soluble in 0.1 N HCl and methylene chloride.
Janssen-Ortho Inc markets extended release formulations of paliperidone, under the trade name of Invega® and are available in strengths of 1.5 mg, 3 mg, 6 mg and 9 mg. The said formulation employs an osmotic drug-release technology (OROS) to provide a "gradual ascending" drug delivery to minimize fluctuation in peak to trough concentration and permits 24 hour dosing interval.
WO2004010981 and EP1539115 disclose extended release formulations and methods for providing ascending rate of release of paliperidone utilizing a capsule-shaped tablet for once a day dosing. The dosage form utilizes a semipermiable membrane surrounding a three layer core: i) the first layer contains drug and an osmotic agent; ii) the middle layer contains higher amount of drug and without osmotic agent and iii) the third layer is a push layer containing osmotic agent. The capsule shaped tablet contains at least one orifice, which is drilled through the membrane on the first drug layer.
U.S. patent application 2006034927 discloses a paliperidone dosage form for sustained release of paliperidone comprising:    a delay layer comprising (i) a polymeric matrix, and (ii) microencapsulated drug, wherein the delay layer is substantially free of non-microencapsulated drug;    a second layer comprising (i) a polymeric matrix, and (ii) non-microencapsulated drug matrix; wherein the second layer is located adjacent to the delay layer.
U.S. patent application 20040092534 and U.S. patent application 20090202631 disclose a method for treating a condition responsive to paliperidone. The dosage form comprises:    (a) a capsule shaped tablet core comprising plurality of layers wherein at least one layer is a drug composition layer containing an active agent and at least one other layer comprises a suitable fluid-expandable polymer;    (b) a semipermeable membrane surrounding the capsule shaped tablet core to form a compartment having an osmotic gradient to drive fluid from an external fluid environment contacting the semipermeable membrane into the compartment; and    (c) an orifice formed through the semipermeable membrane and into the capsule shaped tablet core to permit the active agent to be released from within the compartment into the external fluid environment;    wherein the dosage form releases the active agent at a substantially ascending release rate for a prolonged period of time.
WO2009025859 relates to an extended release inlay tablet of paliperidone. The inlay tablet comprises at least an inlay core and outer layer wherein the inlay core comprises non-coated paliperidone and at least one polymer capable of swelling upon hydration and delaying the release of paliperidone from the inlay core. The inlay core optionally further comprises coated paliperidone. The outer layer partially surrounds the inlay core and comprises a pharmaceutical excipient which is substantially water insoluble.
WO2009109993 relates to extended release matrix compositions of micronized paliperidone, matrix agent and surfactant. The matrix agent is selected from insoluble release controlling agent or hydrophilic release controlling agent or fatty release controlling agent. In these compositions the surfactant and micronized paliperidone are essentially used to enhance the solubility of paliperidone. The particle size distribution of paliperidone is such that 90% particles of paliperidone are less than 30 micron, preferably less than 20 micron and more preferably less than 10 micron.
WO2010009900 relates to a solid pharmaceutical composition comprising monolithic matrix system (MMS) and/or multiparticulate matrix system (MPMS) comprising paliperidone and matrix forming agent. The matrix forming agent is more preferably present in an amount from 60-98% w/w of matrix particles that prolongs the release of paliperidone. The average particle diameter of paliperidone is in the range of 1-250 μm, preferably 5-150 μm. The composition further comprises surfactant and water penetration enhancer to improve the solubility of paliperidone.
WO2009026621 relates to particulates of paliperidone, or pharmaceutically acceptable salts thereof, having D50 particle size distribution of between about 1 micron to about 40 micron.
The compositions of the above mentioned prior art have one or more of the following essential requirements:    1. Use of surfactant and water penetration enhancer;    2. Use of excipient like osmogent;    3. Use of release controlling agent (matrix forming agent) which is preferably at least 60% by weight;    4. Additional process step of drilling an orifice through the semipermeable membrane to enable the release of drug from the system.

Stabilized prolonged release pharmaceutical composition comprising atypical antipsychotic


An electrical motor for a submersible well pump assembly has a brush for preventing arcing across the bearings. The motor has a housing and a stator stationarily mounted in the housing. A shaft extends through a cavity in the stator, the shaft carrying a rotor. Bearings are located at the base and head of the pump for stabilizing the shaft in the housing. A brush is stationarily carried by the housing in electrical common with the stator in the housing. The brush is also in sliding engagement with the shaft. The brush is located near one of the ends of the housing to reduce arcing across the bearing because of voltage differential between the shaft and the stator.

Electrical submersible pumps are used for high volume well production. A submersible pump assembly of this type has a centrifugal pump with a large number of stages. The pump is driven by an electrical motor located below the pump and protected by a seal section which contains thrust bearings for pump thrust. The electrical motor is an AC motor supplied with power from the surface through a cable. The entire assembly is mounted on tubing within a cased well.
The motor is typically 30 feet or more. A rotor mounted to a shaft rotates within a stationary stator to drive the pump. A number of radial bearings are located along the length of the motor for radially stabilizing the rotor. A thrust bearing for rotatably supporting the weight of the rotor is located at the top or head of the motor. In tandem motor assemblies, a thrust bearing is located at the head of the lower motor. The motor is filled with a dielectric lubricant.
Because of the high electrical power supplied to the stator, a magnetic field is generated which causes voltage to be induced into the shaft. At times, the voltage buildup can create a differential between the shaft and the stator or housing that is sufficiently high to cause an electrical arc between the rotating and nonrotating components of the bearings.

Electrical shaft grounding brush assembly and holder for a submersible pump motor


The invention provides systems, associated component parts, and assemblies of the pre-filtration systems, that are useful for treating storm water entering underground storm water management systems. The invention further provides methods to pre-filter storm water prior to entering underground water management systems. The invention reduces pollutant loading in storm water runoff with minimal footprint, flexibility of use and ease of maintenance.

Nearly any new development of land must incorporate a system for managing water run-off from the developed land. Current regulatory schemes typically require developers to install underground water detention and/or retention systems that effectively maintain a flow of water into and off of the developed land that mimics the natural (i.e., pre-development) flow from the land.
Such systems typically are installed under large concrete or asphalt surfaces and often must be capable of bearing highly variable weight loads (e.g., a parking lot). Ideally, such systems should maximize water storage while occupying as small a "footprint" as possible in order to minimize land usage.
In addition, urban and suburban landscapes generate a variety of contaminants that can enter storm water, polluting downstream receiving waters. Many regulatory schemes require not only controlling water run-off, but also water quality. Typically, developed land accumulates pollutants that can contaminate water run-off, particularly after storms. The entrance of gross pollutants, such as trash, debris and coarse sediments, into typical storm water filtration systems is known to reduce efficiency, increase maintenance frequency of the storm water filtration systems, and escalate the costs.
Ideally, underground water management systems should pre-treat water flow from the developed land prior to releasing it. Pre-filtration systems may be used to separate and retain gross pollutants from the filtering systems. They also can be used to capture and retain sediment, oils, metals, and other constituents found in storm water. Such pre-filtration systems should be incorporated into the underground water retention or detention system to minimize land usage, but also should be accessible for intermittent cleaning, repair, and/or other maintenance.
Generally, large (normally pre-cast concrete) pre-filtration structures are installed next to or along the side of the underground water detention or retention system. The pre-filtration structures are connected to the underground water detention or retention system by piping. This type of pre-filtration structure requires additional material and labor costs. It also requires the use of more space to accommodate the pre-treatment structure that sits next to or along the side of the underground water detention or retention system.


A voltage generating circuit includes a first storage unit, a second storage unit, and a voltage generator. The first storage unit stores first voltage data, and the second storage unit stores second voltage data. The voltage generator generates a voltage corresponding to one of the first and the second voltage data according to whether the second voltage data is changed from the first voltage data.

The present disclosure relates to a liquid crystal display (LCD) and, more particularly, to a common voltage generating circuit of an LCD.
Recently, as electronic devices have become lightweight and slim, display devices are also required to be lightweight and slim. In order to meet such requirements, a variety of flat panel displays are being rapidly developed and popularized to replace conventional cathode-ray tube (CRT) displays.
A liquid crystal display (LCD) is one of the flat panel displays mentioned above. In the LCD, a common electrode, a color filter, and alignment layer, and so on are formed on an upper substrate, whereas thin-film transistors, pixel electrodes, and alignment layer, and so on are formed on a lower substrate, and a liquid crystal material with dielectric anisotropy is injected between the alignment layer of the upper substrate and the alignment layer of the lower substrate. A predetermined voltage is applied to the pixel electrode and the common electrode to create a predetermined electric field, and the created electric field changes the orientations of the liquid crystal molecules to adjust the light transmittance of the liquid crystal, so that an image may be displayed.
The LCD is thin and light and, thus, is easy to miniaturize. In addition, the LCD has a low driving voltage and a low power consumption and can provide an image quality close to that of the CRT display. Therefore, the LCD is widely used in a variety of devices, such as mobile communications terminals, monitors and notebook computers. In particular, most of the mobile communication terminals, represented by mobile phones, use the LCD as a display device.
In general, the LCD is driven by applying a predetermined range of voltages to data lines, to which the liquid crystal can respond with the respect to a common voltage applied to the common electrode of the upper substrate. If the LCD continues to respond in only one direction, it is degraded in performance. In order to prevent such performance degradation, data voltages that are inverted with respect to the common voltage are applied to the data lines of the LCD.
The common voltage is one of the most important factors that determines the image quality of the LCD. In general, before the shipment of the LCD, the common voltage is adjusted to an optimal value and the optimal common voltage is stored in a register. The system including the LCD is then programmed for optimal display using the optimal common voltage value stored in the register.
The manufacturing environment of an LCD may change due to the movement or expansion of the manufacturing process line after the initial shipment stage. This process instability may change the optimal common voltage that determines the characteristics of the LCD. Typically, it is difficult to store the changed optimal common voltage in the register. The reason for this is that the system program must also be changed when the changed optimal common voltage is stored in the register. This causes a load on the implementation of the system including the LCD. What is therefore required is an approach to setting the common voltage automatically, without changing the system program.

Liquid crystal display and common voltage generating circuit thereof


Device and method for degassing and dispensing bone cement that can be used to produce a bone cement that is largely free of air inclusions. The device contains a dispensing tube (1) that comprises at least one section (2,3) that is permeable to gas, but impermeable to bone cement. The bone cement is being moved along the gas-permeable section which causes the gas present in the bone cement to flow through the gas-permeable material.

The use of PMMA bone cements is based on the pioneering work of Sir Charnley (Charnley, J.: Anchorage of the femoral head prosthesis of the shaft of the femur. J. Bone Joint Surg. 42 (1960) 28-30.). The structure of PMMA bone cements has remained basically the same ever since. PMMA bone cements consist of a liquid monomer component and a powder component. The monomer component generally contains the monomer, methylmethacrylate, and an activator (N,N-dimethyl-p-toluidine) dissolved therein. The powder component consists of one or more polymers that are made by polymerisation, preferably suspension polymerisation, based on methylmethacrylate and co-monomers, such as styrene, methylacrylate or similar monomers, a radio-opaquer, and the initiator, dibenzoylperoxide. Mixing the powder component and the monomer component, a dough that can be shaped plastically is generated by swelling of the polymers of the powder component in the methylmethacrylate. In this context, the activator, N,N-dimethyl-p-toluidine, reacts with dibenzoylperoxide forming radicals in the process. The radicals thus formed trigger the radical polymerisation of the methylmethacrylate. Upon advancing polymerisation of the methylmethacrylate, the viscosity of the cement dough increases until the cement dough solidifies.
Polymethylmethacrylate bone cements can be mixed by mixing the cement powder and the monomer liquid in suitable mixing beakers with the aid of spatulas. This procedure is disadvantageous in that air inclusions may be present in the cement dough thus formed and cause destabilisation of the bone cement later on. For this reason, it is preferred to mix the bone cement powder and the monomer liquid in vacuum mixing systems. Mixing in a vacuum allows air inclusion to largely be removed from the cement dough and optimal cement quality to thus be attained (Breusch S. J. et al.: Der Stand der Zementiertechnik in Deutschland. Z Orthop. 1999, 137: 101-07). Bone cements mixed in a vacuum have clearly reduced porosity and thus show improved mechanical properties. Various vacuum cementing systems have been described of which only the following shall be named for exemplary purposes: U.S. Pat. No. 6,033,105, U.S. Pat. No. 5,624,184, U.S. Pat. No. 4,671,263, U.S. Pat. No. 4,973,168, U.S. Pat. No. 5,100,241, W99/67015, EP1020167, U.S. Pat. No. 5,586,821, EP1016452, DE3640279, WO94/26403, EP0692229, EP1005901, U.S. Pat. No. 558,745, U.S. Pat. No. 5,344,232.
Aside from removing air or gas inclusions through mixing in vacuo, DE430223005 proposes in addition to also use a vacuum to collect the polymethylmethacrylate bone cement that has been mixed in a vacuum. Said system largely prevents air inclusions in the cement which arise when the polymethylmethacrylate bone cement dough collect at the head end of the cartridges and the remaining residual air between the cement dough and the plunger at the cartridge head is expelled together with the polymethylmethacrylate bone cement dough through the dispensing dispensing tube.
Another concept for attaining a polymethylmethacrylate bone cement that is largely free of air inclusions is used in the Palamix® vacuum cementing system made by Heraeus Medical GmbH, Hanau, that is currently commercially available. In this cementing system, a gas-permeable pore disc is situated in the cartridge head. The air that is present can escape through said pore disc when the polymethylmethacrylate bone cement dough is being dispensed. How-ever, said concept cannot be used with vacuum cementing systems, in which the pore disc is integrated into the plunger.
Aside from the polymethylmethacrylate bone cement that are produced based on powder and liquid, cements made from pastes are also known. According to the invention, the term, polymethylmethacrylate bone cement, includes all production forms of cements, in particular polymethylmethacrylate bone cements made from pastes aside from the cements made from powder and liquid, such as are described, e.g., in DE 102007050762 B3.
It is therefore the object of the invention to provide a simple and safe device and a method for dispensing polymethylmethacrylate bone cements that allow a polymethylmethacrylate bone cement dough that is largely free of air inclusions to be produced.


A method for helping to control a vehicle occupant protection device (22) includes taking an image of the vehicle interior with a digital imager (50) having an array of pixels (53). A contiguous portion of the image less than the entire image is selected. At least one image enhancement technique is applied to the selected image portion. The enhanced image portion is combined with the other portions of the image to make an enhanced image. The enhanced image is analyzed to detect at least one of features and characteristics of the enhanced image. Alternatively, a selected non-contiguous group of the pixels (53) of the imager (50) are read out, as representative of the entire image, to estimate the illumination levels across the entire array of pixels. In one aspect, the imager shutter (56) speed may be controlled to enhance the image.

1. Technical Field
The present invention relates to image analysis and image enhancement. In particular, the present invention relates to the analysis and enhancement of images taken of a vehicle interior for the purpose of helping to control a vehicle occupant protection device.
2. Description of the Prior Art
It is known to take images of a vehicle interior for the purpose of helping to control a vehicle occupant protection device. For example, it is known to take an image of the area of a vehicle seat, to help decide whether to actuate a vehicle occupant protection device. If the seat is determined to be empty, the device (for example, an air bag) may not be actuated; or, if it is determined that there is a child or a child seat present on the vehicle seat, the device may not be actuated.
It is known to use a charge coupled device (CCD) imager to take such images of a vehicle interior, and to direct the output of the imager, a set of pixel values, into a classifier to process the images.

Enhancement of vehicle interior digital images


Disclosed herein is an apparatus for processing information about a network including a plurality of nodes, wherein m attributes (m represents an integer of 2 or more) assignable to each of the nodes are defined depending on the relationship to another node which can be connected to the each of the nodes, the apparatus including: identifier generating means for converting attributes assigned to each of n nodes (n represents an integer of 3 or more) per relationship to the other node connected thereto into numerical values with respect to motifs extracted from the network as predetermined patterns of the connected relationship of the n nodes, and generating identifiers identifying the motifs using the numerical values.

1. Field of the Invention
The present invention relates to an information processing apparatus and method, and a program, and more particularly to an information processing apparatus and method, and a program for analyzing a network in a short time through an easy process.
2. Description of the Related Art
In recent years, efforts have been made to research and develop the technology for analyzing a network of interconnected protein molecules (hereinafter referred to as "protein network"). For example, R. Milo, S. Itzkovitz, N. Kashtan, R. Levitt, S. Shen-Orr, I. Ayzenshtat, M. Sheffer, and U. Alon, "Superfamilies of designed and evolved networks", Science, 303: 1538-42 (2004) (hereinafter referred to as Non-Patent Document 1) discloses the technology for measuring the frequency of occurrences of patterns (hereinafter referred to as "motifs" or "Motifs") of three interconnected nodes, each representing a protein, in a protein network.
According to the related art including the Non-Patent Document 1, a large expenditure of time and labor is taken to analyze a protein network because there are many types of proteins to be handled as nodes.
For example, it is important to extract major partial structures from a protein network in knowing the causal association of functions of proteins and also in contributing to estimating carcinogenic processes in cancer research and finding cancer treatment points. It is also of importance to investigate the roles of nodes (to act on other nodes) and determine what types of proteins exist as nodes having those roles, from the extracted major partial structures.
If a protein network is analyzed according to the related art including the Non-Patent Document 1, then a large expenditure of time and labor is taken simply to detect the frequency of occurrences of motifs. Furthermore, a subsequent process of extracting motifs that occur highly frequently as major structures and of investigating the roles of nodes (to act on other nodes) in those motifs and determining what types of proteins exist as nodes having those roles is also in need of a huge expenditure of time and labor.
The problems described above with respect to the analysis of a protein network are also applicable to the analysis of other networks made up of a number of nodes.
According to an embodiment of the present invention, it is desirable to provide an information processing apparatus and method, and a program for analyzing a network in a short time through an easy process.

Information processing apparatus and method, and program