A semiconductor memory device has sets of address fuses which are arranged in a plurality of fuse rows in order to provide a larger number of redundant elements. The sets of address fuses are associated with addresses, respectively, and at least one address fuse included in each of the sets of the address fuses is provided in only one of the fuse rows. Address buses are provided such that the number of address lines associated with the sets of the address fuses is less than the number of fuse rows. One of the address lines is located closer to one of the fuse rows which includes associated address fuses than a center line between the one of the fuse rows and another one of the fuse rows which is adjacent to the one of the fuse rows is. The address lines are connected to redundant element control circuits through local lines.

The present invention relates to a semiconductor memory device, and in particular, an improvement of a redundancy technique for a DRAM in which address fuses are arranged in a form of a plurality of stages of row.
In the technical field of a semiconductor device, elements to be incorporated into a semiconductor chip have been formed to have a smaller size, thus increasing the number of elements incorporated into one semiconductor chip. This has been accompanied by an increase in the number of defects in the elements. Furthermore, due to dusts or impurities fallen onto a portion of the memory cell array of the semiconductor chip, a large size of defect has occurred in the elements on the memory cell array portion. These element or elements are referred to as defective element or elements hereinafter.
However, the yield was low just after such smaller semiconductor elements had been developed or at the beginning of their mass production. To solve this problem, a technique for providing a redundant element control circuit has been proposed, and put to practical use (hereinafter this technique will be referred to a redundancy technique). In the redundancy technique, redundant elements are prepared on the supposition that the semiconductor device has defective elements. To be more specific, if a defective element is detected in a manufactured memory cell array, a redundant element is used instead of the defective element. That is, when an input address signal for designating the defective element is inputted, a redundant element is selected instead of the defective element.
Such a technique is the above-mentioned redundancy technique. By virtue of the redundancy technique, even if a semiconductor device includes a defective element, it can be used as a non-defective semiconductor device by employing a redundant element instead of the defective element.
The defective elements may cause in a row (word line). The defective elements may cause in a column (bit line pair). The defective elements may cause in a plurality of rows (word lines). The defective elements may cause in a plurality of columns (bit line pairs). Accordingly, the redundant element or elements mean element or elements contained in a row (word line), element or elements contained in a column (bit line pair), element or elements contained in a plurality of rows (word lines), or element or elements contained in a plurality of columns (bit line pairs). That is, the redundant element or elements mean element or elements contained in a row (word line) as a unit, element or elements contained in a column (bit line pair) as a unit, element or elements contained in a plurality of rows (word lines) as a unit, or element or elements contained in a plurality of columns (bit line pairs) as a unit.
The size of the semiconductor chip is slightly increased when the redundancy technology is incorporated thereinto. However, the yield is greatly improved, since as explained above, a semiconductor device is employed as a non-defective device even if it includes a defective element.
FIG. 9 illustrates a redundant element control circuit. A plurality of the redundant element control circuits are provided for the respective redundant elements. Addresses are programmed to each of redundant element control circuit to designate a corresponding redundant element. Thus, when an input address signal is inputted to the redundant element control circuits, a corresponding redundant element control circuit is selected and activated in response to the input address signal to select the corresponding redundant element.
The redundant element control circuit 6 comprises a fuse latch circuit group 4 and a comparator 5 which will be explained later with reference to FIG. 12. The fuse latch circuit group 4 includes a plurality of fuse latch circuits, which are required to select an associated redundant element. Each of the fuse latch circuits is illustrated in FIG. 10, and thus will be explained with reference thereto as follows:
The fuse latch circuit, as shown in FIG. 10, comprises a PMOS transistor Tr1, an NMOS transistor Tr2, an inverter INV1, an inverter INV2, a transmission gate Tr3, a transmission gate Tr4, and an address fuse 3. The transmission gate Tr3 is constituted by a parallel circuit comprising a PMOS transistor and an NMOS transistor. Also, the transmission gate Tr4 is constituted by a parallel circuit comprising a PMOS transistor and an NMOS transistor.
An initializing signal X is inputted to the gate of the PMOS transistor Tr1, and an initializing signal Y is inputted to the gate of the NMOS transistor Tr2. The source of the PMOS transistor Tr1 is connected to power supply potential, and the drain of the PMOS transistor Tr1 is connected to the drain of the NMOS transistor Tr2. The source of the NMOS transistor Tr2 is connected to an address fuse FAi, and then connected to ground potential by the address fuse FAi. An input terminal of the inverter INV1 is connected to a common drain node of the transistors Tr1 and Tr2. Also, an output terminal of the inverter INV2 is connected to the common drain node of the transistors Tr1 and Tr2. An output terminal of the inverter INV1 is connected to an input terminal of the inverter INV2.
The gate of the PMOS transistor of the transmission gate Tr3 and the gate of the NMOS transistor of the transmission gate Tr4 are also connected to the common drain node of the transistors Tr1 and Tr2. The gate of the NMOS transistor of the transmission gate Tr3 is connected to the output terminal of the inverter INV1. To be more specific, the gate of the PMOS transistor of the transmission gate Tr3 and the gate of the NMOS transistor of the transmission gate Tr4 are connected to the common drain node of the transistors Tr1 and Tr2, and the gate of the NMOS transistor of the transmission gate Tr3 and the gate of the PMOS transistor of the transmission gate Tr4 are connected to the output terminal of the inverter INV1.
An address ADD<i> is inputted to the transmission gate Tr3 from an address line of an address bus through a local line, and an address /ADD<i> is inputted to the transmission gate Tr4 from another address line of the address bus through another local line. The character "/" represents a logical inversion signal (complementary signal). Address ADD<i> is outputted from the transmission gate Tr3 as an output FOUT<i>, or address /ADD<i> is outputted from the transmission gate Tr4 as an output FOUT<i>.
In the fuse latch circuit 4, when power is supplied, the initializing signals X and Y, which are illustrated in FIG. 11, are inputted to the gate of the PMOS transistor Tr1 and the gate of the NMOS transistor Tr2, respectively, and the fuse latch circuit 4 is thus initialized. When the input address signal is changed, ADD<i> is outputted from the transmission gate Tr3 or /ADD<i> is outputted from the transmission gate Tr4, as the output FOUT<i> of the fuse latch circuit 4. Whether ADD<i> is outputted or /ADD<i> is outputted depends on whether or not the fuse FAi is cut.
The comparator 5, as shown in FIG. 12, comprises a NAND circuit on its input side and a NOT circuit on its output side. The NOT circuit is series-connected to the NAND circuit. When the number of addresses required to select a redundant element is n+1, the NAND circuit receives FOUT<0> to FOUT<n>. When all FOUT<0> to FOUT<n> are at 1 level, the comparator 5 generates a redundant element enabling signal ENABLE, to thereby activate an associated redundant element. When the associated redundant element is activated, a memory element connected thereto is activated.
As explained above, the redundant element control circuits each having a fuse latch circuit group 4 and a comparator 5 are provided for the respective redundant elements. The fuse latch circuit group 4 comprises a plurality of fuse latch circuits, which are required to select an associated redundant element. Each of the fuse latch circuits includes an address fuse FA (FIG. 8), which is associated with an address to be programmed thereto. Therefore, if the number of redundant elements is increased, the total number of address fuses is also increased, and thus the address fuses cannot be arranged in one row. Therefore, in the conventional semiconductor memory device, the address fuses are arranged in a form of a plurality of fuse rows (stages), e.g., two fuse rows 1 and 1' (two stages) as shown in FIG. 8. Address lines of an address bus are provided in a region between adjacent two of the fuse rows, e.g., in a region between the fuse rows 1 and 1' as shown in FIG. 8.
In the conventional semiconductor memory device, when the address fuses are arranged in a form of a plurality of fuse rows (stages), e.g., two fuse rows, a plurality of sets of the address fuses, which are respectively associated with the redundant elements, are divided into two groups (two rows), and each of the address fuse sets is provided in any one of two rows, as shown in FIG. 13. The address fuses of each address fuse set are associated with addresses for designating a corresponding redundant element. In the example of FIG. 13, a fuse set 2 (including fuses FA0, FA1, FA2 . . . FAn) associated with a redundant element is provided in a fuse row 1 (the first stage), and a fuse set 2' (including fuses FA0, FA1, FA2 . . . FAn) associated with another redundant element is provided in a fuse row 1' (the second stage). That is, a plurality of address fuses associated with the same address are arranged in both of the two fuse rows 1 and 1'.
In the conventional semiconductor memory device, two address lines are provided for the fuse rows 1 and 1', respectively, as shown in FIG. 14, in the case where it is difficult to provide a layout of local lines from an address line to the fuse latch circuits, e.g. 4n, of the redundant element control circuits. In other words, the memory device needs two address lines one of which is for the fuse row 1 and the other is for fuse row 1' (in the case where the input address signal is a complementary address signal, four address lines are needed two of which are for the fuse row 1 and the other two are for fuse row 1'). Address lines A0, A1, A2 . . . An (six address lines in the example shown in FIG. 14) are provided for the fuse row 1, and address lines A0, A1, A2 . . . An (six address lines in the example of FIG. 14) are provided for the fuse row 1'. Accordingly, in the example of FIG. 14, the two address lines are provided to each of the addresses, as a result of which the region occupied by the address lines is great, thus increasing the address line area on the semiconductor chip. Furthermore, the consumption of current for driving the address lines is large since the number of address lines is large. In addition, the capacitance of the address lines is increased, and thus the address transition speed is lowered, and as a result the speed of selection of a redundant element is also lowered, as long as the sizes of address drivers provided for driving the address lines are not increased.
Moreover, there is a case where as shown in FIG. 15, it is possible to provide a layout of the local lines from one address line to the fuse latch circuits of the redundant element control circuits, whose address fuses are arranged in the form of two rows 1 and 1'. In this case, the address lines A0, A1, A2 . . . An (six address lines in the example shown in FIG. 15) are provided between the two fuse rows 1 and 1', as common address lines. To be more specific, the common address lines are used commonly for both the fuse rows 1 and 1', and thus connected commonly, by the local lines, to the fuse latch circuits 4i of the redundant element control circuits on the sides of the fuse rows 1 and 1'. However, the local lines must be extended from the common address lines toward the fuses 1 and 1', respectively. They must have great lengths. As a result, the parasitic capacitance of the local lines connected to the address lines is increased, and thus the consumption of current for driving the address lines is also increased. Consequently, the transition speed of the input address signal is lowered, and that of selection of a redundant element is also lowered, as long as the sizes of the address drivers are not increased.

Semiconductor memory device with redundancy control circuits


Methods, systems, and media for relighting images using predicted deep reflectance fields are provided. In some embodiments, the method comprises: identifying a group of training samples, wherein each training sample includes (i) a group of one-light-at-a-time (OLAT) images that have each been captured when one light of a plurality of lights arranged on a lighting structure has been activated, (ii) a group of spherical color gradient images that have each been captured when the plurality of lights arranged on the lighting structure have been activated to each emit a particular color, and (iii) a lighting direction, wherein each image in the group of OLAT images and each of the spherical color gradient images are an image of a subject, and wherein the lighting direction indicates a relative orientation of a light to the subject; training a convolutional neural network using the group of training samples, wherein training the convolutional neural network comprises: for each training iteration in a series of training iterations and for each training sample in the group of training samples: generating an output predicted image, wherein the output predicted image is a representation of the subject associated with the training sample with lighting from the lighting direction associated with the training sample; identifying a ground-truth OLAT image included in the group of OLAT images for the training sample that corresponds to the lighting direction for the training sample; calculating a loss that indicates a perceptual difference between the output predicted image and the identified ground-truth OLAT image; and updating parameters of the convolutional neural network based on the calculated loss; identifying a test sample that includes a second group of spherical color gradient images and a second lighting direction; and generating a relit image of the subject included in each of the second group of spherical color gradient images with lighting from the second lighting direction using the trained convolutional neural network.

Photo-realistic relighting of human faces is a highly sought after feature with many applications ranging from visual effects to truly immersive virtual experiences. That said, human users are often capable of distinguishing real faces from synthetic renderings. Thus, photo-realistically relighting any human face is indeed a challenge with many difficulties including modelling sub-surface scattering and blood flow to estimating the interaction between light and individual strands of hair, and as a result is laborious and computationally intensive. Further, many current methods require a large set of input images, and so are unsuitable for use with moving or dynamic subjects.
Accordingly, it is desirable to provide new methods, systems, and media for relighting images using predicted deep reflectance fields.


A device that sucks small quantities of air through a lit cigar in order to maintain sufficient oxygen flow to prevent the cigar from going out.

Cigar smoking is a peaceful pastime that has been carried on for generations. In a pre-civil war ballad, entitled "My Last Cigar" or "Twas Off the Blue Canaries," James M. Hubbard paid homage to the final puffs of his last cigar while on a ship at sea. The existence of such a ballad attests to the pleasure people obtain from smoking cigars.
Many interesting things have been devised by people to extinguish a cigar when the cigar smoker cannot continue such a pleasurable activity. For example, if one wished to quickly snuff or extinguish the cigar, the methods of U.S. Pat. Nos. 4,907,604 and 5,862,809 would accomplish such a feat. Such patents disclose extinguishing the cigar rapidly using an airtight cap over the lit end of the cigar, thereby forcing the smoker to relight the cigar. However, as any cigar aficionado knows, such relighting has deleterious affects on the taste and flavor of the cigar.
U.S. Pat. Nos. 6,145,510 and 6,089,236 describe other interesting things that try to control the burn rate of a lit cigar using a cigar holding device with adjustable vents to control the flow of air to the lit cigar. However, both devices will sooner or later result in the cigar being extinguished.
Another interesting thing was described in U.S. Pat. No. 3,978,981. This patent describes a tubular receptacle with air vents that allows to transport a lit cigar. However, the cigar would eventually be extinguished if the smoker does not puff the cigar.
U.S. Pat. No. 6,584,982 describes an interesting thing that marks cigarettes for use in a smoking machine.
An interesting thing was described in U.S. Pat. No. 4,198,992. This interesting thing is a smoker's appliance that keeps a cigarette lit using a flexible bulb that is attached to a body that, upon squeezing, forces air into a cylindrical body to keep the cigarette lit. U.S. Pat. No. 6,615,840 describes an interesting thing that is an electrical smoking system for smoking a cigarette. This interesting thing keeps a cigarette lit using a lighter that has a heating blade and a controller.
While the aforementioned devices and methods may be interesting things, none describe a device that keeps the cigar lit throughout its burn and prevents the cigar from being extinguished. Such a device should keep a cigar lit without requiring the smoker to puff the cigar.
The present invention solves these problems by providing a device or a holder that actively sucks air through a lit cigar to simulate the puffs of the smoker. The holder applies suction at the unlit end of the cigar, therefore allowing air to flow through the cigar to prevent self-extinguishing of the cigar. Using such a device, the smoker does not need to puff the cigar in order to keep the cigar burning. Such a device is indeed a very interesting thing.

Device to avoid auto-extinguishing of cigars


The present invention relates to the biological and pharmacological effects of placental protein 13 (PP-13), an effect that may be used as a treatment and/or prevention of preeclampsia and placental insufficiencies, in pregnant female mammals, especially pregnant women. The invention relates to a method to treat female mammals with the purpose to precondition the uterine arteries and prevent and/or reverse the pathological conditions associated with placental insufficiency such as preeclampsia, HELLP and/or eclampsia.

Preeclampsia is a syndrome defined by hypertension and proteinuria developed after twenty (20) weeks of gestation that also may be associated with myriad other signs and symptoms, such as oedema, visual disturbances, elevated liver enzyme, hemolysis, low platelets, headaches, and epigastric pain [1]. One sub-form of the disease, denoted HELLP, standing for hemolysis, elevated enzyme liver and low platelets, can occur with or without hypertension, and the term preeclampsia include this sub-form throughout this document. This disease complicates 3-7% of all pregnancies and is a multisystem maternal disorder that is the most common cause of death for both children and mothers during pregnancy. While the clinical manifestations appear from week 20, the underlying mechanisms may begin as early as at the time of implantation. As the disease progresses the disease may develop into its severe type called eclampsia, caused by angiospasmus in the brain and brain oedema that may result in severe epileptic seizures, stroke and death.
The etiology for preeclampsia is unknown but it is believed that during placentation, the invasion by the placental cells, the trophoblasts, into the uterus wall layer of the spiral arteries appears to be incomplete [2-3] and the severity of hypertension may be related to the degree of trophoblastic invasion [4]. Vasoconstriction and elevated resistance to blood flow follows as a consequence. The etiology is also described as decreased placental perfusion (or placental insufficiency), in combination with oxidative stress that causes general endothelial cell damage within the placenta which may result in endothelial inflammation, affecting the maternal vascular system and the vascularization of the kidneys.
About one third of cases develop in the first pregnancies. Other risk factors include multifetal gestations, conceiving through in-vitro fertilization, particularly oocyte donation, preeclampsia and hypertension disorders in a previous pregnancy, family history of preeclampsia, chronic hypertension, pregestational diabetes, vascular and connective tissue disease, nephropathy, antiphospholipid antibody syndrome, systemic lupus erythematosus (SLE), obesity, age 35 years and older, teenagers and African-American race [5]. Preeclampsia is a leading cause of maternal mortality and morbidity accounting for about 12-18% of all pregnancy-related maternal deaths. It is also associated with a high perinatal mortality and morbidity. The only curative treatment for preeclampsia today is to deliver the fetus and removal of the placenta.
Mothers who develop preeclampsia at pregnancy are at increased risk for cardiovascular diseases and diabetes, and their offsprings are at risk for obesity and diabetes, in addition to developmental disorders such as motor and cognitive disorders and blindness.
Reduced uterine perfusion associated with increased vascular resistance can be detected with Doppler ultrasound of the maternal uterine arteries. The increased impedance to the uterine artery perfusion, or increased pulsatility index and Doppler notch indicates that the mother may have a higher risk of developing preeclampsia, resulting in various endothelial problems such as a general endothelial inflammation. The symptoms of preeclampsia typically appear in the third trimester of pregnancy and are usually detected by routine monitoring of the woman's blood pressure and urine proteins
Currently, there are no known cures for preeclampsia except for delivery of the fetus. However, the decision to deliver a patient with preeclampsia must balance both maternal and fetal risks. Preeclampsia can vary in severity from mild to life threatening. A mild form of preeclampsia can remain mild with bed rest and frequent monitoring. For moderate to severe cases, hospitalization is necessary and blood pressure medication and anticonvulsant medications to prevent seizures are prescribed. If the condition becomes life-threatening to the mother or the baby, the only cure is to terminate the pregnancy often resulting in a prematurity of the newborn due to the pre-term delivery. There are two main goals of management of women with preeclampsia: prevention of seizures or eclampsia and control of hypertension. Magnesium sulfate has been used for the prevention of seizures, usually as an intravenous delivery. Daily calcium supplementation and early use of Aspirin may reduce the frequency of the disorder particularly if administered before 16 weeks. Antioxidant vitamins have not been shown to prevent preeclampsia. The management of blood pressure levels with the drugs labetalol or hydralazine has shown benefits although to a limited time.
Novel biomarkers have been found that may be used to detect the syndrome. One such is expressed in the placenta already during the first trimester and may be used to predict pregnancies at risk, a protein called placental protein 13 (PP-13) [6]. The concentration of PP-13 has been shown to be altered in maternal blood in pregnancy disorders such as preeclampsia. More recent studies have shown that the serum levels of PP-13 are significantly reduced at 6-13 weeks in cases developing early, as well as late-onset preeclampsia [7]. PP13 is a member of the β-galactoside binding S-type galectin superfamily and is only expressed in placental tissues of higher primates, and within the villous trophoblast it can only be found in the multinucleated syncytiotrophoblast [8]. PP-13 is expressed and released into the intervillous space, where it enters the maternal circulation and can be detected in maternal blood. While in unaffected pregnancies serum concentrations of PP-13 rise moderately from the first to the third trimester of pregnancy, women who develop preeclampsia start with a lower than normal PP-13 level in the first trimester, and a diagnostic test was develop to use the lower PP-13 level as a measure to predict high risk for preeclampsia. PP-13 levels sharply increase between the first to the third trimester in women who enter the active phase of the disease. This stip change in the level of PP-13 is further assisting in predicting the risk to develop the disorder

Biological activity of placental protein 13


An apparatus is provided for generating a generalized linear model structure definition by generating a gradient boosted tree model and separating each decision tree into a plurality of indicator variables upon which a dependent variable of the generalized linear model depends. A first number of plurality of decision tree structures each having a maximum tree depth of one (1) is formed, where the first number represents a number of decision tree structures necessary to exhaust all main effects of a plurality of predictor variables on a dependent variable. Successive pluralities of decision tree structures each having a maximum tree depth increased by one (1) as compared to its immediately preceding plurality of decision tree structures are iteratively formed. Each successive plurality of decision tree structures comprises a second number of decision tree structures necessary to exhaust all interactions between the plurality of predictor variables.

A Generalized Linear Model (GLM) is a statistical model which relaxes or removes several of the assumptions required by a least-squares linear regression. The flexibility thus gained makes the Generalized Linear Model (GLM) suitable for application to a larger set of data types and prediction problems. As a statistical model, a Generalized Linear Model (GLM) favors analytical rigor and clarity of interpretation over the exhaustive maximization of predictive accuracy. A skilled practitioner must specify which variables will contribute to the model's prediction, and the form of their relationship with the quantity to be predicted. In addition to being very labor intensive, this manual specification process tends to overlook some variables and combinations of variables which could improve the predictive accuracy of the Generalized Linear Model (GLM).
Gradient boosting is a machine learning technique for regression and classification problems which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do, and it generalizes them by allowing optimization of an arbitrary differentiable loss function. For example, gradient boosting combines weak learners into a single strong learner in an iterative fashion. Gradient boosting tends to aggressively exploit any opportunity to improve predictive accuracy, to the detriment of clarity of interpretation (or, indeed, the feasibility of any interpretation whatsoever).
Applicant has identified a number of deficiencies and problems associated with existing techniques involving generalized linear models (GLMs) and gradient boosting. Through applied effort, ingenuity, and innovation, many of these identified problems have been solved by developing solutions that are included in embodiments of the present disclosure, many examples of which are described in detail herein.

Training gradient boosted decision trees with progressive maximum depth for parsimony and interpretability


A semiconductor device includes a base substrate and first and second semiconductor wires which are arranged side by side on the base substrate, and the base substrate is provided with an opening (inter-wire grove, slit) in an extending direction of the first and second semiconductor wires between the first semiconductor wire and the second semiconductor wire.

1. Technical Field
The present invention relates to a semiconductor device, a method of manufacturing a semiconductor device, and an electronic apparatus, and particularly, to a technology of reducing a parasitic capacitance.
2. Related Art
In recent years, technologies of forming a small-sized high-sensitivity semiconductor device on a base substrate using a micro electro mechanical system (MEMS) technology and forming wires which are connected to the semiconductor device on the base substrate together with the formation of the semiconductor device have attracted attention.
As such a method of manufacturing a semiconductor device, for example, a silicon substrate which is a material of a semiconductor device is bonded to a base substrate made of glass or the like through anodic bonding, and subjected to etching except for an area which forms constituent elements of the semiconductor device of the silicon substrate and an area which forms semiconductor wires which are connected to the constituent elements to die-cut the constituent elements and the semiconductor wires to thereby obtain a semiconductor device.
In addition, as another manufacturing method, in DENSO Technical Review, Vol. 5, No. 1, 2000, pages 39 to 44, a silicon-on-insulator (SOI) substrate is used as a base substrate for a semiconductor device, and a configuration is disclosed in which in a semiconductor device having constituent elements arranged on a SOI substrate, wires made of polysilicon for connection to constituent elements are embedded in the SOI substrate and connected to constituent elements of connection destinations. In DENSO Technical Review, Vol. 5, No. 1, 2000, pages 39 to 44, the SOI substrate has a SiO2 layer which is positioned below the position at which the wires are embedded.
However, the wires are arranged adjacent to the glass substrate of SiO2 or the SiO2 layer in any of the above-described methods. SiO2 has a high specific permittivity. Accordingly, when the wires are arranged adjacent to SiO2, a parasitic capacitance (stray capacitance) is easily generated between the wires. Accordingly, in any method, there is a tendency that electrical characteristics of the semiconductor device are adversely affected due to the parasitic capacitance between the wires.

Semiconductor device, method of manufacturing semiconductor device, and electronic apparatus


A urine disposing apparatus and method utilizes a cart-like structure to permit a bed-ridden patient to utilize a single urinal for multiple urinations. Following each use, the contents of the urinal are poured into a director, from which they empty into a receptacle located within the disposing apparatus. The empty urinal may then be re-used and emptied as needed. After a period of use, a caregiver may remove the receptacle, clean the component portions of the apparatus as required, and re-position the apparatus and empty urinal for use by the patient.

Patients who are confined in a lying position because of infirmity and/or in connection with recovery from surgery or the like are unable to use a standard toilet for purposes of urination. Instead, typically, they must urinate into an open-topped container, known as a urinal. Because the typical patient can be expected to urinate more than a single time in the course of a night, the standard practice is to position several empty urinals in close proximity to the patient. This is often done by hanging empty urinals (which usually have handles) on the bed rail, resting them on a nightstand, or the like.
As each urinal is used, the patient is supposed to place it on a bedside table or similar location, so that it may later be removed by a health care provider. Even where a urinal is not completely filled, a patient will generally be unwilling to further fill it later for fear of spillage, and will instead prefer to position the partially-filled urinal on the table and use an empty urinal for the next urination. As a consequence, at the end of a night, it is not uncommon to find three or four full or partially full urinals on the patient's bedside table.
The need to deal with a plurality of urinals in various states of fullness can be cumbersome for a patient. It is frequently the case that urinals are knocked over, causing the spilling of urine onto the patient, his clothes, and his bedding. Of course, such an event can be extremely upsetting and unpleasant to the patient, and can even be physically harmful to the patient's skin.
A need exists for a urine disposing apparatus and method that permits a patient to utilize a single urinal for multiple voids, with the urinal being capable of being placed by the patient into an empty condition prior to each use. The present invention satisfies this need and provides other, related, advantages.


An optical filter device has a light interference filter and a casing. The light interference filter has a fixed substrate, a movable substrate joined to the fixed substrate, a fixed reflection film provided on the fixed substrate, and a movable reflection film provided on the movable substrate. The casing has a base substrate and a lid that forms an internal space with the base substrate. The movable substrate has a holding portion provided on a surface opposite to the fixed substrate, outside a light interference region, as viewed in a plan view. The base substrate has a light transmission hole corresponding to a light transmission region. An outer peripheral edge of the light transmission hole faces the holding portion. The surface opposite to the fixed substrate of the movable substrate is joined to the base substrate.

1. Technical Field
The present invention relates to an optical filter device, an optical module, and an electronic apparatus.
2. Related Art
Traditionally, a variable-wavelength interference filter in which reflection films are arranged to face each other via a predetermined gap, on surfaces facing each other of a pair of substrates, is known. Also, an optical filter device having such a variable-wavelength interference filter housed in a casing is known (see, for example, JP-A-2008-70163).
The optical filter device disclosed in JP-A-2008-70163 has a package (casing) that includes a plate-like pedestal (base substrate) and a cylindrical cap. In this casing, a peripheral edge portion of the base substrate and one end portion of the cylinder of the cap are welded or bonded and thus connected together, and a space for housing the variable-wavelength interference filter is provided between the base substrate and the cap. A hole is provided in a top surface of the cap that is opposite to the pedestal, and a window portion for transmitting light is provided in this hole.
By the way, a light transmission hole may be provided not only in the cap as in JP-A-2008-70163 but also in the base substrate. However, parallelism of the base substrate may be impaired in the processing to form the light transmission hole or the like. For example, a curvature, protrusion or the like is generated near an outer peripheral edge of the light transmission hole. If the base substrate with the impaired parallelism and the variable-wavelength interference filter are joined together, the curving part or protruding part locally contacts the joining surface of the variable-wavelength interference filter and therefore prevents horizontal fixture of the variable-wavelength interference filter. Consequently, there is a problem that resolution is lowered.

Optical filter device, optical module, and electronic apparatus


An OBI manager provides the reduction/elimination of optical beat interference (OBI). As will be described in more detail below, the OBI manager identifies OBI partners through an identification process performed via an RFoG network. An OBI partner may be two optical networking units (ONUs) that may interfere with one another when transmitting in the same time slot. Once the OBI partners are identified, the OBI manager may perform a mitigation process to mitigate possible OBI. For example, the OBI manager may organize the OBI partners to reduce OBI, such as by guaranteeing no OBI partners transmit at the same time.

Several network types exist for delivering media content, such as video, data, voice, or high-speed Internet services, for example, to subscribers. In a cable television (CATV) network, for example, the network may take the form of an all-coax, all-fiber, or hybrid fiber/coax (HFC) network, delivering media content from a headend to subscriber client devices. In addition to transporting data traffic, as well as television content signals over a CATV network, multiple services operators (MSO) also use their network infrastructure for carrying voice, video on demand (VoD) and video conferencing traffic signals, among other types.
Radio Frequency (RF) over Glass (RFoG) is a fiber to the home (FTTH) technology that may operate concurrently with an HFC network, such as out of the same headend/hub in a cable network. RFoG permits the continued use of traditional HFC equipment and back-office applications with fiber-to-the-premise deployments. For example, RFOG enables cable operators to reuse existing headend equipment and infrastructure of Data Over Cable Service Interface Specification (DOCSIS) service delivery. Thus, use of existing cable modem termination system (CMTS) platforms, headend equipment, set-top boxes, and cable modems can continue while gaining benefits inherent with RFoG systems. For example, concurrent RFOG/HFC operation enables the use of RFoG for node splitting, which may increase capacity in an existing HFC network.
A phenomenon called optical beat interference (OBI) may occur in RFoG systems when two return transmitters hit a receiver simultaneously on the same wavelength. In a cable system, for example, the condition that causes OBI can easily occur in multiple-dwelling unit (MDU) applications of DOCSIS-based systems with bonded upstream channels. OBI can potentially impact the entire return path performance and will become an increasing concern as return path bandwidth and utilization grows.

Optical beat interference detection and mitigation


An optimum image selection method for a digital photograph device selecting an optimum image by driving a vibration detection sensor mechanism is provided. In continuous photography mode, as soon as capturing an image, it detects and records the vibration amount of the image, and then compares the presently detected vibration amount with the vibration amount of the image which is stored formerly, and if the vibration amount detected presently is smaller, the image captured presently will be stored, so the clearest image will be distinguished and retained immediately by using the vibration amount.

1. Field of the Invention
The present invention relates to an optimum image selection method and system, in particular, to an optimum image selection method and system in a digital photograph device.
2. Description of Related Art
In a conventional digital photograph device, e.g. digital camera (hereunder taking digital camera for example), in the aspects of operation and design, the objective is all to obtain images with clear and high quality. Presently, to achieve such an objective, it is generally by means of improving optical, mechanical and electrical elements therein. In addition to the above-mentioned approaches, it is also possible to use continuous photography mode to further select clearer images from a series of continually captured images.
The digital camera currently available on the market, when operating in optimum selection continuous photography, mostly compresses the captured images then saves them continually in memory so as to efficiently use the storage space. Upon the end of photography process, it then takes the captured images from the memory, and after decompression process, proceeds to analyze image clarity, compares these images, then saves the image of highest clarity and deletes the remaining ones with less satisfactory quality.
However, the aforementioned image analysis approach is not able to determine the image quality immediately, since such a process consumes a relatively longer time, and requires larger memory volume to store the captured intermediate images.

Optimum image selection method and system


An electron beam device having a specimen holder, in particular for a transmission electron microscope (TEM), which makes it possible to identify the specimen holder in a simple manner is described. Therefore, the electron beam device has at least one specimen holder having at least one holding element for holding a specimen and at least one identification unit. Furthermore, the electron beam device has a reading unit for reading the identification unit without contact, a goniometer, into which the specimen holder may be inserted, and a controller for controlling the movement modes of the goniometer, via which the movement modes of the goniometer are controlled on the basis of the identification data supplied by the identification unit and of corresponding data stored in the controller.

1. Technical Field
The present invention relates to an electron beam device having a specimen holder, in particular a transmission electron microscope (TEM).
2. Description of Related Art
Specimen holders which are used in electron beam devices have for long had a tiltable design. Tilting a specimen to be examined is advantageous in different examination methods used in the case of an electron beam device. A goniometer is typically used for angle adjustment. However, specimen holders from different manufacturers have different maximum tilt angles. Because different specimen holders are used in electron beam devices depending on the specimen to be examined and the examination method used, the movements of the goniometer are a function of a specimen holder used in an electron beam device. In particular, the tilt angle of certain specimen holders is limited as a function of the objective lens of the electron beam device and of the movement axis set by a user.
To identify different specimen holders, the method of mounting contacts on the specimen holder for holder indexing, which are brought into contact with contacts of a plug connector, is known to date. The specimen holder is identified via the indexing. It is, however, disadvantageous here that the plug-in connector must always be plugged in. Furthermore, it is disadvantageous that users often use specimen holders from different manufacturers. One problem is that the manufacturers of the individual specimen holders must agree on a single indexing system; otherwise errors in the assignment and identification of the individual specimen holders and thus in the adjustment of the tilt angle may occur when reading the indexing. Another problem is that the design and performance of some electron beam devices are only suited for receiving specimen holders from a single manufacturer to ensure sufficiently good functioning and regular operation of the electron beam device.
Alternatively, a method is known in which data belonging to a sample holder must be queried by the control software of the electron beam device or a goniometer mounted thereon when changing the sample holder and accordingly must be input by the user. Incorrect inputs entailing serious consequences for the sample holder and/or the objective lens are thus possible.
It would be desirable to provide an electron beam device having a specimen holder which makes it possible to identify the specimen holder in a simple manner.

Electron beam device having a specimen holder


In response to a first user becoming active on a communication device, a first availability status can be automatically established as a current availability of the first user. A first time period can be automatically identified. During the first time period, the first availability status can be maintained as the current availability of the first user to at least a second user. In response to the first time period elapsing, a second availability status can be automatically established as the current availability of the first user to the second user.

Often, when a user of an instant messaging (IM) system becomes available, she is suddenly inundated with messages from people who have been waiting for her to appear online. This may occur when she first logs onto the IM system, when her status on the IM system changes from "away" to "available", when her status changes from "in a meeting" to "available", and so forth. The problem is compounded further in systems which automatically notify other users when a user has become available, for instance in response to a request by such other users. This service is sometimes referred to as a "camp-on" service. Such circumstances often discourage a user from logging onto her IM system for fear of being overwhelmed by messages.
Some IM systems allow a user to log onto the system with a particular status of her choice. That is, rather than logging onto the system with an "available" status, the user can log on with another status, for instance "away". If the user later wishes to make her presence known to other IM users, she must remember to change her status to "available", in which case she again risks being inundated with messages.

Managing a communication availability status

International Business Machines Corporation


A new and distinct Nandina cultivar named ‘TWILIGHT’ is disclosed, characterized by distinctive pink, white and green foliage, which changes color with maturity. Plants have unique pink colored stems and petioles on new growth. The new cultivar is a Nandina, suitable for ornamental garden purposes.

The new cultivar is a product of chance discovery by the inventor. This new variety, hereinafter referred to as 'TWILIGHT', was discovered as a naturally occurring, whole plant mutation by the inventor, Neil Marek. The interesting new mutation was discovered in a commercial laboratory in Magnolia, Tex. among a population of Nandina domestica 'Gulf Stream', U.S. Plant Pat. No. 5,656 during May of 2010.
After identifying the new variety as a potentially interesting selection, the inventor first organized propagation of 'TWILIGHT' by tissue culture at the same commercial laboratory during May of 2010. The inventor continued controlled testing and propagation, assessing stability of the unique characteristics of this variety. At least five generations have been reproduced and have shown that the unique features of this cultivar are stable and reproduced true to type.


A vertical PNP transistor (11) and method for making it includes forming an N- region (19) in a P substrate (12), and forming an N+ region (26) in the substrate (12) laterally surrounding and partially extending into the N- region (19). A P region (30) is formed above the N- region (19), bounded laterally by the N+ region (26) to be horizontally and vertically isolated from the substrate (12) by the N- and N+ regions (19 and 26). A layer of semiconductor material (32) is formed overall, and an N well (35) and a surrounding P well (36) are formed, each extending to the P region (30). An isolating N+ well (38) is formed surrounding the P well (36), extending to the buried N+ region (26). A P emitter region (40) and an N base contact region (41) are formed at a surface of the N well (35), and a P collector contact region (44) is formed at a surface of the P well (36). Preferably, a CMOS structure (10) may be constructed elsewhere on the substrate concurrently with at least some of the steps for making the isolated vertical PNP transistor (11). For example, in one embodiment, the step of forming a P emitter region (40), an N base contact region (41), and a P collector contact region (44) are performed as a part of the simultaneous formation of source and drain regions (47 and 48) of the CMOS structure (10) elsewhere on the substrate (12). In another embodiment, the step of forming an N base contact (54) and a P collector contact (53) are performed as a part of a simultaneous formation of source and drain regions of a CMOS structure elsewhere on the substrate. In this embodiment, a separate deeper a P emitter region (52) is formed in the N well (19) to increase the emitter X.sub.J.

1. Field of the Invention
This invention relates to improvements in vertical PNP transistors and methods for making same in digital BiCMOS processes, and more particularly to improvements in methods for building high F.sub.t, isolated, vertical PNP transistors in standard non-oxide-isolated digital BiCMOS twin well DUF (buried layer) processes.
2. Relevant Background
An accelerating trend in the integrated circuit industry is the merging of analog and digital functions onto the same semiconductor substrate on which an integrated circuit is constructed. Factors such as overall system speed, reliability, and board space are all involved in forcing this trend. In these so-called "mixed-signal" designs, the digital content is usually much higher than the analog content. Consequently, the choice of integrated circuit process technology usually involves adding the necessary analog components onto an existing digital manufacturing process.
Digital BiCMOS processes are usually the starting process of choice, since they combine the CMOS components for digital applications together with high-speed (F.sub.t .gtoreq.10 GHz) NPN devices needed for the analog functions. However, most digital BiCMOS processes emphasize bipolar NPN devices, without providing a suitable isolated PNP device. If any such PNP device is available, it is typically a lateral PNP device, which is very slow, with F.sub.t values in the range of about 10 MHz. Therefore, such PNP devices are generally not suitable for use in the signal path, hampering the ability to design cost-effective high-speed analog functions.
The concept of integrating isolated vertical PNP transistors into an existing junction-isolated BiCMOS process is addressed in U.S. Pat. No. 4,855,244 by Hutter and Trogolo, which describes a LinBiCMOS process. While this patent discusses the use of an N- buried layer region for vertically isolating a P-type DUF region from a P-type substrate, the description is in the context of a standard N+ buried layer process, rather than a twin well DUF process.
What is needed, therefore, for mixed-signal process technologies is a low cost method for building high F.sub.t, isolated, vertical PNP transistors in a standard non-oxide-isolated digital BiCMOS twin well DUF process.

Method for making isolated vertical PNP transistor in a digital BiCMOS process


A method and system for detecting coincidences in a data set of objects, where each object has a number of attributes. Iteratively, equally-sized subsets of the data set of sampled, and coincidences (co-occurrences of a plurality of attribute values in one or more objects in the subset) are recorded. For each coincidence of interest, the expected coincidence count is determined and compared with the observed coincidence count; this comparison is used to determine a measure of correlation for the plurality of attributes for the coincidence. The resulting set of k-tuples of correlated attributes is reported, a k-tuple of correlated attributes being a plurality of attributes for which the measure of correlation is above a predetermined threshold. The method and system (implemented on an array of processing nodes) is suitable for protein structure analysis, e.g. in HIV research.

The invention relates to methods, devices and systems for coincidence detection among a multitude of variables. In addition, the invention relates to applying coincidence detection methods to various fields, and to products derived from such application.
k-tuples of Correlated Attributes
The discovery of correlations among pairs of k-tuples of variables has applications in many areas of science, medicine, industry and commerce. For example, it is of great interest to physicians and public health professionals to know which lifestyle, dietary, and environmental factors correlate with each other and with particular diseases in a database of patient histories. It is potentially profitable for a trader in stocks or commodities to discover a set of financial instruments whose prices covary over time. Sales staff in a supermarket chain or mail-order distributor would be interested in knowing that consumers who buy product A also tend to buy products B and C, and this can be discovered in a database of sales records. Computational molecular biologists and drug discovery researchers would like to infer aspects of 3D molecular structure from correlations between distant sequence elements in aligned sets of RNA or protein sequences.
One formulation of the general problem which encompasses many diverse applications, and which facilitates understanding of the principles described herein is a matrix of discrete features in which rows correspond to xe2x80x9cobjectsxe2x80x9d (such as individual patients, stock prices, consumers, or protein sequences) and the columns correspond to features, or attributes, or variables (such as lifestyle factors, stocks, sales items, or amino acid residue positions).
Mathematical methods for determining a measure of the type, degree, and statistical significance of correlation between any two, or even three or four, particular variables are widespread and well-understood. These methods include linear and nonlinear regression for continuous variables and contingency table analysis techniques for discrete variables. However, great difficulties arise when one tries to estimate correlationxe2x80x94or just estimate joint or conditional probabilitiesxe2x80x94over much larger sets of variables. This intractability has one main causexe2x80x94there are too many joint attribute-value probability density termsxe2x80x94and this manifests itself in two serious problems: (1) computing and storing frequency counts over all terms, over the database, requires too much computation and memory; (2) there is usually an insufficient number of database records to support reliable probability estimates based on those frequency counts.
Let us consider some details. For M records (objects), N variables (attributes, fields), and supposing that each variable has the same set of |A| possible values, there are             (      k      )        N    =            N      !                                (                      N            -            k                    )                !                          k        !
k-tuples of columns. Adding the number of k-tuples for each k=1, 2, . . . , NA results in 2Nxe2x88x921 such tuples of all sizes. This exponential complexity has been a major obstacle standing in the way of higher-order probability estimation and correlation detection methodologies.
One natural way to think about this complexity is in terms of the power set of the set of column variables. This power set forms a mathematical lattice under the operation ⊂, a xe2x80x9ctowerxe2x80x9d corresponding to a graph whose nodes are subsets of this set of column variables. (Note that if a set has N members, the power set has 2N members). From this viewpoint, two nodes representing subsets "sgr"1 and "sgr"2 are connected if and only if either "sgr"1⊂"sgr"2 or "sgr"2⊂"sgr"1. We say that "sgr"2""s node is above "sgr"1""s if "sgr"1⊂"sgr"2. This gives a natural meaning to the term xe2x80x9chigher-orderxe2x80x9d, as appearing higher up the tower. We call the bottom, the null set node, the 0th tier; the single column terms from the first tier, and so on.
Continuing with the tower analogy, we note that each xe2x80x9cfloorxe2x80x9d of this edifice contains       (    k    )    N
xe2x80x9csuitesxe2x80x9d, and each suite contains |A|k xe2x80x9croomsxe2x80x9d. In other words, the kth level of the lattice corresponds to       (    k    )    N
different k-tuples of column variables, and associated with each k-tuple is an (|A| by |A| . . . by |A|/) contingency table, each cell of which must store the counted frequency of a particular joint symbol (ai1, ai2, . . . , aik) were one to use a classical contingency table test for the correlation between those particular k columns. (See FIG. 1a).
For any k∈{1, 2, . . . , N}, for any particular k-tuple of columns (cj1, cj2, . . . , cjk), there are |A|k possible joint values. For any k∈{1, 2, . . . , N}, for any particular k-tuple of columns (cj1, cj2, . . . , cjk), the estimation of Kullback divergence or other correlation function using the dataset is at least an xcexa9(Mk) or xcexa9(|A|k) computation, depending upon the relative sizes of M, k and |A|.
A comprehensive probabilistic model of the database must be able to specify probability estimates for       ∑          k      =      1        N          xe2x80x83                        (        k        )            N                          "LeftBracketingBar"        A        "RightBracketingBar"            k
terms. This means, for example in the computational molecular biology domain, that for a tiny heptapeptide sequence family, each sequence having a length of seven amino acid residues, there are 1,801,088,540 terms to specify. For an unrealistically small RNA of fifteen nucleotides in length, over the smaller RNA alphabet of four base symbols, there are 30,517,578,124 terms.
Clearly the models can become intractably huge. What about the space of possible models through which a modelling/learning procedure must search? Consider a latent-variable model, which seeks to explain correlations between sets of observable variables by positing latent variables whose states influence the observables jointly. Since each model must specify a set of k-tuples of variables, and there are exp(2, 2N) (i.e., 2 to the power 2N) such sets, there are exp(2, 2N) possible models in the worst-case search space.
Various methods for determining a measure of higher-order probabilities will circumvent the combinatorial explosion through severe prior restrictions on the width k (See FIG. 3a), the locality (FIG. 2a), the number, or the degrees of correlation of the higher-order features sought, and on the kinds of models entertained (See FIG. 4a).
Three Goals of Probability Estimation
It is useful, before discussing details of existing methods and of the current invention, to delineate three different possible goals of probability estimation in large datasets, each corresponding to a large body of research and current practice:
1. Estimation of the fully-specified, fully higher-order joint probability distribution: Estimate a probability density q that specifies
q(ai1@ci1, ai2@ci2, . . . , aik@cik)
xe2x80x83for all k-tuples of attributes and possible values.
2. Hypothesis testing, for particular hypotheses concerning particular attributes and particular variables: For example, are the data consistent with the hypothesis that columns ci1, ci2, . . . , cik are independent?
3. Feature detection, or xe2x80x9cdata miningxe2x80x9d: Detect the most suspicious coincidences, for example, joint attribute occurrences that are more probable than would be predicted from lower-order marginals. Related to this, find the most highly correlated k-tuples of columns.
It is the feature detection and data mining applications that are most relevant to the present invention. However, some of the most successful ways to estimate a full higher-order joint probability distribution of a database require the specification of exactly those higher-order terms which represent high correlations among sets of kxe2x89xa72 variables and invoking maximum entropy assumptions, and therefore the current invention is aimed at those applications as well.
Related Work
Various mathematical and computational methods have been proposed and used to estimate higher-order probabilities, to detect correlations, and to model higher-order database relationships. All such prior methods either perform a global, sometimes exhaustive search through all possible k-tuples of variables, which is too costly, or they avoid the complexity altogether by limiting their search to only k-tuples of a specific fixed, small size k. (Often, k=2 so only pairwise correlations are ever considered).
Below are listed some representative examples of related work.
Assuming Independence between Attributes. The easiest way to avoid the complexity of higher-order correlations is just to pretend that they do not exist. Many of the algorithms and computer programs, historically dominant in some fields of application of the current method, simply construct and use a model of the data in which all variables, all attributes, are independent. For example, the modelling of DNA and protein sequences, in computational molecular biology, is often done with consensus sequences and profiles, which assume incorrectly that the different base or amino acid residue positions are independent. Reliance on such models can obscure crucial functional and structural insights into the DNA or proteins being modelled.
Prior Limits on k. One proposal for Gibbs models of databases is based on the use of Gibbs potentials, and it proposes a hashing method for calculating these special terms. Each kth-order potential requires an estimation of a kth-order joint probability density as well as some number of lower-order (typically k-/th-order) densities. The asymptotic time complexity of Miller""s pattern-collection subroutine, the major component of the potential calculation, is, when interpreted in our terminology:       M    ·                  ∑                  k          =          1                K                          xe2x80x83                                                N            A                                (            k            )                                            2          k                      ≈      O              (              MN                              xe2x80x83                              K                    )
where K=kmax is the highest order of features for which one will search and by which one will represent database objects. This exponential blow-up prevents one from searching for higher-order features (HOFs) of any order k much higher than 4 or 5 in databases with hundreds of attributes.
Many methods, in different application areas, simply limit k to k=2. For example, pairwise inter-residue correlation methods discover second-order features that can be useful in the prediction of protein structure and function and that can be built into classifiers more sensitive that first-order sequence classifiers and fold-recognizers. To the extent that k-ary interactions are important, and to the extent that such interactions leave traces in sets of homologous sequences, the pairwise methods are deficient. One can try to infer k-ary correlations from sets of 2-ary correlations [9] (essentially by computing the transitive closure of the xe2x80x9cCorrelatesWithxe2x80x9d binary relation), but this heuristic can lead to trouble: high pairwise correlations among variables x, y, z do not in general imply, nor are they necessarily implied by, a high 3-ary correlation (as measured by Kullback divergence) of the three variables x, y, z. In other application areas, such as the study of multiple drug interactions, it is similarly true that important higher-order relationships can be missed by pairwise correlation detection methods.
The Paturi et al. Method for Identifying the Most Correlation Pair of Random Variables. A method has been reported for the problem of finding the most highly correlated pair Xi, Xj of variables from among a large set of N random binary variables X1, X2, . . . , XN. The method is easily extended to finding the most correlated k-tuple of random binary variables, but at a significant increase in computational complexity, and only for kxe2x89xa72 fixed a priori. It uses a definition of correlation that has Correlation (Xi, Xj)=P[Xi=Xj] over some sets of M samples {Xm1, Xm2, . . . , XmN}m=1,2, . . . , M. (Here P[Xi=Xj] means xe2x80x9cthe probability that variable Xi has the same value, or state, as variable Xj). Much of the computational complexity, both time complexity and sample complexity, of their method can be incurred in trying to separate two or more nearly equally-correlated pairs (or k-tuples) of variables.
The two variants of the Paturi method are asymptotically quadratic and subquadratic in N, respectively, the faster procedure requiring more sampling. When the method is extended to search for the biggest k-ary correlation, where correlation is now defined as P[Xi1=Xi2= . . . =Xik], the time complexity grows to approximately O(k2Nklog3N). Search for highly correlated attribute cliques of width k much greater than 5 or 6 in very large datasets is once again ruled out.
Hidden Markov Models. Hidden Markov Models (HMMs) have been used widely and with increasing success in recent years, in both automatic speech recognition and in the modelling of protein, DNA, and RNA sequences.
Although some groups have reported significant success in modelling protein sequence families and continuous speech data with HMMs, nonetheless there are great improvements to be made in learning time and model robustness by the xe2x80x9chardwiringxe2x80x9d of pre-selected higher-order features into HMMs. (This has been investigated for HMM-like recurrent neural networks, in different domains).
Some of the same reasons why HMMs are very good at aligning the protein sequences or recorded utterances in the first place, using local sequential correlations, make such methods less useful for finding the important sequence-distant correlations in data that has already been partially or completely aligned. The phenomenon responsible for this dilemma is termed xe2x80x9cdiffusionxe2x80x9d.
A first-order HMM, by definition, assumes independence among sequence columns, given a hidden state sequence. Multiple alternative state sequences can in principle be used to capture longer-range interactions, but the number of these grows exponentially with the number of k-tuples of correlated columns.
The Agrawal et al. Method for Discovery of Association Rules. This method was developed in perhaps the purest data mining context, the automatic extraction of knowledge-base rules from databases. It considers a database of M transactions (objects, rows) and N items (attributes, columns) and seeks to extract rules of the form a= greater than b. It therefore seek pairs of attributes a, b such that xe2x80x9ctransactions that contain a tend to contain bxe2x80x9d, hence those pairs with high values for p(b|a). xe2x80x9cPeople who buy CD players tend to buy CDsxe2x80x9d, is just one example suggesting the potential commercial interests in such methods. (More generally, one can search for sets of attributes with high p(b1, b2, . . . , bk|a1, a2, . . . , aj)).
A rule a= greater than b is said to have:
1. confidence c if c % of transactions containing a also contain b (hence, roughly, if                     (                              p                                      (                              a                ,                b                            )                                            p                                      (              a              )                                      )            ≥              c                  (          100          )                      )    ;
2. support s if s % of transactions contain a and b (hence, roughly, if                     p                          (                      a            ,            b                    )                    ≥              s        100              )    .
The goals behind this method are different from the objectives of the current invention. However, the different objectives are brought closer together if one focuses on the Agrawal method""s discovery of symmetric rules (so that the search is for attribute pairs displaying high values for both                               p                                (                          a              ,              b                        )                          a                          xe2x80x83                  and                    xe2x80x83                                    p                                (                          a              ,              b                        )                          b              )    ,
and if one reduces the emphasis on support (so that coincidences that are suspicious, even if occurring rarely, are sought).
The Agrawal method is shown to have O(∥S∥xc2x7MN) time complexity, where ∥S∥ is the sum of all values Support (xcex1) for an exponentially large number of k-tuples xcex1 of attributes, of any size 1xe2x89xa6kxe2x89xa6N, that reach a particular stage of processing in this procedure. Hence the method is O(2N) in the worst case. A series of empirical tests are performed on what they considered to be realistic datasets for their domain. The running time of the procedure grew only linearly with the number M of transactions, but the number of items, or attributes, was held constant at NA=1000, and their constructed datasets probably contained no correlated k-tuples of width k greater than 10. An analysis of their algorithm, which is based on an incremental build-up of kth-order cliques from k-/th-order cliques, makes clear that the method takes much more computation to find wide HOFs (large k) than narrower HOFs (lower k) of equivalent statistical significance.
Steeg, Robinson, Deerfield, Lappaxe2x80x941993. Some rough, heuristic methods have been presented for finding k-tuples of correlated residues (positions) in sets of aligned protein sequences. One of the presented methods employed one embodiment of a rudimentary version of the representation and detecting coincidences steps of the described herein.
Alternative methods of, and devices for, finding correlations between attributes, and applications for those correlations, are required.
In a first aspect the present invention provides a coincidence detection method for use with a data set of objects having a number of attributes. The base method includes the following steps:
representing a set of M objects in terms of a number NA of variables (xe2x80x9cattributesxe2x80x9d), where an attribute is said to occur in an object if the object possesses the attribute;
sampling a subset of ri out of the M objects, for each iteration among a predetermined number of iterations;
detecting and recording coincidences among sets of k of the attributes in each sampled subset of objects, a coincidence being the co-occurrence of 1xe2x89xa6kxe2x89xa6NA attributes in the same hi out of ri objects in the sampled subset, where 0xe2x89xa6hixe2x89xa6ri;
determining an expected count of coincidences for any set of k attributes and a predetermined number of iterations of sampling and coincidence-counting as described above, the determining being performed before sampling and collecting, at the same time or after sampling and collecting;
comparing, for any set of k attributes and number of iterations of sampling and coincidence-counting, the observed count versus the expected count of coincidences, and from this comparison determining a measure of correlation (or association, or dependence) for the set of k attributes; and
reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a set of k of the NA attributes which have been determined by this process to have a value for a chosen correlation measure above a predetermined threshold value.
In a second aspect the invention provides a coincidence detection method for use with a data set of objects having a number of attributes, the method comprising the steps of:
sampling a subset of the data set for a predetermined number of iterations, each iteration the sampled subset of the data set having for each object the same subset of attributes;
detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset of the data set being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence; and
reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In any of its aspects the comparison of observed and expected counts may be calculated using a Chernoff bound on tail probabilities, and counts may be recorded by storing a running total of the count of each coincidence over all of the sampled subsets.
In a third aspect the invention provides a method for visual exploration of a data set of objects having a number of attributes, the method comprising the steps of:
sampling a subset of the data set for a predetermined number of iterations, each iteration the sampled subset of the data set having the same number of objects although not necessarily the same objects and having for each object the same subset of attributes;
detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset of the data set being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence; and
reporting a set of k-tuples of correlated attributes to a user through a graphical interface, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In a fourth aspect the invention provides a pre-processing method for use with a data modelling unit to capture and report to the data modelling unit higher order interactions of a data set of objects having a number of attributes, the method comprising the steps of:
sampling a subset of the data set for a predetermined number of iterations, each iteration the sampled subset of the data set having for each object the same subset of attributes;
detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence; and
reporting to the data modelling unit a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In a fifth aspect the invention provides a correlation elimination method for use with a data set of objects having a number of attributes, the method comprising the steps of:
sampling a subset of the data set for a predetermined number of iterations, each iteration the sampled subset of the data set having for each object the same subset of attributes;
detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence; and
eliminating a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In any of the aspects, the objects may be sales transactions, each transaction comprising one or more purchased products, and the attributes may be instances of sale of particular products or types of products. The objects may be time slices and the attributes may be the status of elements in a system. The objects may be time slices and the attributes may be prices, or price changes of, financial instruments or commodities.
In any of the aspects the steps of the method may be represented by the following pseudo-code:
0. begin
1. read (MATRIX);
2. read (R, T);
3. compute_first_order_marginals(MATRIX);
4. csets :={};
5. for iter=1 to T do
6. sampled_rows :=rsample(R, MATRIX);
7. attributes :=get_attributes(sampled_rows);
8. all_coincidences :=find_all_coincidences(attributes);
9. for coincidence in all_coincidences do
10. if cset_already_exists(coincidence, csets)
11. then update_cset(coincidence, csets);
12. else add_new_cset(coincidence, csets);
13. endif
14. endfor
15. endfor
16. for cset in csets do
17. expected :=compute_expected_match_count(cset);
18. observed :=get_observed_match_count(cset);
19. stats :=update_stats(cset, hypoth_test(expected, observed));
20. endfor
21. print_final_stats(csets, stats);
22. end
In a sixth aspect the invention provides a coincidence detection system for use with a data set of objects, each object having a plurality of attributes, the system comprising:
means for sampling a subset of the data set for a predetermined number of iterations, each iteration the sampled subset of the data set having for each object the same subset of attributes;
means for detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
means for determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
means for comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence; and
means for reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In the system of the sixth aspect, the means for sampling a subset of the data set may comprise means for dividing the data set into subsets for sampling. The means for detecting and recording counts of coincidences may comprise an array of processing nodes, each processing node detecting and recording a respective subcount of coincidences, and the means for comparing, for each coincidence of interest, said observed count of coincidences to said expected count of coincidences may comprise means for merging said subcounts to provide said observed count. At least one of said processing nodes may comprise a respective subarray of processing nodes that detect and record respective subsubcounts of coincidences, and said means for merging merges said subsubcounts to provide said subcounts and/or said observed count. Each processing node may comprise memory including an input buffer for storing received subsets of the data set and an output buffer for storing the subcount or the subsubcount; and a memory bus that transfers data to and from the memory.
In a seventh aspect the invention provides coincidence detection programmed media for use with a computer and with a data set of objects having a number of attributes, the programmed media comprising:
a computer program stored on storage media compatible with the computer, the computer program containing instructions to direct the computer to:
sample a subset of the data set for a predetermined number of iterations, each iteration the sampled subset of the data set having for each object the same subset of attributes;
detect and record counts of coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determine an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
compare, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determine a measure of correlation for the plurality of attributes for the coincidence; and
report a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In an eighth aspect the invention provides a coincidence detection system for use with a data set of objects having a number of attributes, the system comprising:
a computer; and
a computer program on media compatible with the computer, the computer program directing the computer to:
sample a subset of the data set for a predetermined number of iterations, each iteration the sampled subset having for each object the same subset of attributes,
detect, and record counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determine an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording,
compare, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determine a measure of correlation for the plurality of attributes for the coincidence, and
report a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In any of its aspects the methods of the invention may further comprise the step of
representing the objects and attributes in a matrix of objects versus attributes prior to sampling the data set, the data set being sampled by sampling the matrix.
In a ninth aspect the invention provides a product having a set of attributes selected by:
sampling a subset of a data set representing objects versus attributes for a predetermined number of iterations, each iteration the sampled subset having the same number of objects although not necessarily the same objects and having for each object the same subset of attributes,
detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets,
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording,
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence, and
reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In a tenth aspect the invention provides a product defined by applying a set of rules generated from:
sampling a subset of a data set representing objects versus attributes for a predetermined number of iterations, each iteration the sampled subset having for each object the same subset of attributes,
detecting and recording counts of coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the data set, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets,
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording,
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence, and
reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In any aspect the methods of the invention may further comprise the step of applying rules that are defined by the reported correlated attributes.
In an eleventh aspect the invention provides a peptide or peptidomimetic including a structural motif of the V3 loop of HIV envelope protein including spatial coordinates of residues A18/Q31/H33.
In a twelfth aspect the invention provides a pharmaceutical composition comprising a ligand that interacts with a protein having a structural motif identified using the method of claim 2, and a pharmaceutically acceptable carrier or exicipient therefor. The ligand may comprise chemical moieties of suitable identity and spatially located relative to each other so that the moieties interact with corresponding residues or portions of the motif. The ligand, by interacting with the motif, may interfere with function of a region of the protein comprising the motif.
In a thirteenth aspect the invention provides a diagnostic agent comprising a ligand that interacts with a protein having a structural motif identified using the method of the earlier aspects of the invention, and a detectable label linked to the ligand.
In a fourteenth aspect the invention provides a pharmaceutical composition for interacting with an envelope protein of human immunodeficiency virus (HIV), the envelope protein including a structural motif of the V3 loop having spatial coordinates of residues A18/Q31/H33, comprising a ligand including at least one functional group that interacts with the motif, and a pharmaceutically acceptable carrier or exicipient therefor. The ligand may include at least one functional group capable of binding to and being present in an effective position in said ligand to bind to residue 18, at least one functional group capable of binding to and being present in an effective position in said ligand to bind to residue 31, and at least one functional group capable of binding to and being present in an effective position in said ligand to bind to residue 33.
In a fifteenth aspect the invention provides a method of designing a ligand to interact with a structural motif of an envelope protein of human immunodeficiency virus (HIV), the method comprising the steps of: providing a template having spatial coordinates of residues A18, Q31 and H33 in the V3 loop of HIV envelope protein, and computationally evolving a chemical ligand using an effective algorithm with spatial constraints, so that said evolved ligand includes at least one effective functional group that binds to the motif. The ligand may comprise at least one functional group capable of binding to and being present in an effective position in said ligand to bind to residue 18, at least one functional group capable of binding to and being present in an effective position in said ligand to bind to residue 31, and at least one functional group capable of binding to and being present in an effective position in said ligand to bind to residue 33.
In a sixteenth aspect the invention provides a method of identifying a ligand to bind with a structural motif of an envelope protein of human immunodeficiency virus (HIV), the method comprising the steps of: providing a template having spatial coordinates of A18, Q31 and H33 in the V3 loop of HIV envelope protein; providing a data base containing structure and orientation of molecules; and screening said molecules to determine if they contain effective moieties spaced relative to each other so that the moieties interact with the motif. A first moiety of the molecule may interact with residue 18, a second moiety of the molecule interacts with residue 31 and a third moiety of the molecule interacts with residue 33.
In a seventeenth aspect of the invention the invention may provide antigens and vaccines embodying the covarying k-tuples described herein.
In an eighteenth aspect the invention provides a product being defined by its interaction with a set of attributes selected by:
sampling a subset of a data set representing objects versus attributes for a predetermined number of iterations, each iteration the sampled subset of the data set having the same number of objects although not necessarily the same objects and having for each object the same subset of attributes,
detecting, and recording counts of, coincidences in each sampled subset of the data set, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets,
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording,
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence, and
reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a pre-determined threshold.
In any of the aspects the objects may be compounds and the attributes may comprise particular chemical moieties. The objects may be peptides or proteins and the attributes may comprise particular structural or substructural patterns or motifs. The objects may be selected from the group consisting of compounds, molecular structures, nucleotide sequences and amino acid sequences and the attributes may be features of the selected objects. The objects may be time slices and the attributes may be biological parameters of genes or gene products. The objects may be documents that are electronically stored and/or electronically indexed and the attributes may be topics. The objects may be customers and the attributes may comprise products purchased or not purchased by those customers. The attributes may further comprise mailings made or not made to the customers. The objects may comprise products and the attributes may comprise customers that have or have not purchased those products. The attributes may further comprise demographic variables of the customers. The objects may be people with a particular disease or disorder and the attributes may be potential contributing factors for the disease or disorder. The objects may be people with a number of different diseases or disorders and the attributes may be potential contributing factors for the diseases or disorders. The objects may comprise factors potentially contributing to a disease or disorder and the attributes may be people with or without those factors, in which case the method associates groups of people of substantially equivalent risk for the disease or disorder.
The objects may be time slices and the attributes may comprise the state of components in a system at time slices prior to failure of the system, in which case the method associates component states that may potentially cause failure of the system.
In the first aspect ri may be the same for every iteration.
In any of the aspects the method provided may further comprise the steps of first creating a database of transitions between system states, wherein a system state is represented by a value of a state variable, over a chosen time quantum, and presenting the database, in whole or part, as a data set such that each state to state transition set corresponds to one of M objects and so that each state variable corresponds to an attribute.
In any of its aspects the method provided may further comprise the steps of first creating a database of states and actions covering a chosen time quantum and presenting the database, in whole or part, as a data set such that each state/action/state triple corresponds to one of M objects and so that each state variable or action type corresponds to an attribute.
In a nineteenth aspect the invention provides a coincidence detection method for use with a data set of objects having a number of attributes represented in a matrix of objects versus attributes, the method comprising the steps of:
sampling a subset of the matrix for a predetermined number of iterations, each iteration the sampled subset of the matrix having for each object the same subset of attributes;
detecting, and recording counts of, coincidences in each sampled subset of the matrix, a coincidence being the co-occurrence of a plurality of attribute values in one or more objects in a sampled subset of the matrix, where the plurality of attribute values is the same for each occurrence, the detecting and recording counts of coincidences in each sampled subset being performed before, at the same time or after sampling, detecting and recording counts of coincidences in other subsets;
determining an expected count for each coincidence of interest, the determining being performed before, at the same time, or after sampling, detecting and recording;
comparing, for each coincidence of interest, the observed count of coincidences versus the expected count of coincidences, and from this comparison determining a measure of correlation for the plurality of attributes for the coincidence; and
reporting a set of k-tuples of correlated attributes, where a k-tuple of correlated attributes is a plurality of attributes for which the measure of correlation is above a respective pre-determined threshold.
In the first aspect numerical correlation values may be reported along with the set of k-tuples of correlated attributes.

Coincidence detection method, products and apparatus