mhurhangee/patent-ind-claim-en huggingface dataset:
A negative electrode active material for a lithium secondary battery, the negative electrode active material comprising: 5 parts by weight to 20 parts by weight of a first carbon-based particle based on 100 parts by weight of a total negative electrode active material; 55 parts by weight to 90 parts by weight of a second carbon-based particle based on 100 parts by weight of the total negative electrode active material; and 1 part by weight to 40 parts by weight of a silicon-based particle based on 100 parts by weight of the total negative electrode active material, wherein a specific BET surface area of the first carbon-based particle is 1.5 m 2 /g to 4.5 m 2 /g, a specific BET surface area of the second carbon-based particle is 0.4 m 2 /g to 1.5 m 2 /g, and the specific BET surface area of the first carbon-based particle is greater than the specific BET surface area of the second carbon-based particle. 5 parts by weight to 20 parts by weight of a first carbon-based particle based on 100 parts by weight of a total negative electrode active material; 55 parts by weight to 90 parts by weight of a second carbon-based particle based on 100 parts by weight of the total negative electrode active material; and 1 part by weight to 40 parts by weight of a silicon-based particle based on 100 parts by weight of the total negative electrode active material,
Device for extracting physiological information indicative of at least one vital sign of a subject, said device comprising: - an input interface for obtaining at least two detection signals (C n ) derived from detected electromagnetic radiation transmitted through or reflected from a skin region of a subject, wherein each detection signal comprises wavelength-dependent reflection or transmission information in a different wavelength channel, - a pulse signal computation unit for computing at least two pulse signals (S 1 , S 2 ) from said at least two detection signals (C n ) using different given signature vectors (P bv 1, P bv 2), wherein for the computation of each pulse signal a different given signature vector is used, wherein a given signature vector represents expected relative pulsatilities of the respective pulse signal in the at least two detection signals, wherein the computation of a pulse signal involves computing a weighted combination of the at least two detection signals using weights resulting in a pulse signal for which the products with the original detection signals equals the relative pulsatilities as represented by the respective signature vector, - a quality indicator computation unit for computing quality indicator values (Q 1 , Q 2 ) for said pulse signals (S 1 , S 2 ) indicating a characteristic of the respective pulse signal, and - a processing unit for deriving physiological information (V) indicative of at least one vital sign from the signature vector that results in the pulse signal with the best quality indicator value (Q 1 , Q 2 ) and/or from said pulse signal. - an input interface for obtaining at least two detection signals (C n ) derived from detected electromagnetic radiation transmitted through or reflected from a skin region of a subject, wherein each detection signal comprises wavelength-dependent reflection or transmission information in a different wavelength channel, - a pulse signal computation unit for computing at least two pulse signals (S 1 , S 2 ) from said at least two detection signals (C n ) using different given signature vectors (P bv 1, P bv 2), wherein for the computation of each pulse signal a different given signature vector is used, wherein a given signature vector represents expected relative pulsatilities of the respective pulse signal in the at least two detection signals, wherein the computation of a pulse signal involves computing a weighted combination of the at least two detection signals using weights resulting in a pulse signal for which the products with the original detection signals equals the relative pulsatilities as represented by the respective signature vector, - a quality indicator computation unit for computing quality indicator values (Q 1 , Q 2 ) for said pulse signals (S 1 , S 2 ) indicating a characteristic of the respective pulse signal, and - a processing unit for deriving physiological information (V) indicative of at least one vital sign from the signature vector that results in the pulse signal with the best quality indicator value (Q 1 , Q 2 ) and/or from said pulse signal.
A measurement apparatus comprising a controller configured to control a plurality of different functions (F 1 to F n ) of said measurement apparatus in response to user motion data (UMD) received via an input interface of said measurement apparatus characterized by comprising a configuration memory having for each function (F) of said measurement apparatus at least one associated user (U), wherein if a failure of a function (F) occurs, user motion data (UMD) of each of at least one associated user (U) of said function (F) is retrieved according to data content of a configuration memory and evaluated by the controller to control a reactive function to handle the occurred failure, wherein the failure of the function (F) of the measurement apparatus forms a triggering event which triggers a request to retrieve the user motion data of the associated user (U), and the request is forwarded via a communication network to a mobile device carried by the respective associated user (U), wherein the retrieved user motion data (UMD) of each of the at least one associated user (U) includes a relative position of the user (U) with respect to said measurement apparatus , a moving direction of the user (U), a moving velocity of the user (U) and/or an acceleration of the user (U). a controller configured to control a plurality of different functions (F 1 to F n ) of said measurement apparatus in response to user motion data (UMD) received via an input interface of said measurement apparatus characterized by comprising a configuration memory having for each function (F) of said measurement apparatus at least one associated user (U), wherein if a failure of a function (F) occurs, user motion data (UMD) of each of at least one associated user (U) of said function (F) is retrieved according to data content of a configuration memory and evaluated by the controller to control a reactive function to handle the occurred failure, wherein the failure of the function (F) of the measurement apparatus forms a triggering event which triggers a request to retrieve the user motion data of the associated user (U), and the request is forwarded via a communication network to a mobile device carried by the respective associated user (U), wherein the retrieved user motion data (UMD) of each of the at least one associated user (U) includes a relative position of the user (U) with respect to said measurement apparatus , a moving direction of the user (U), a moving velocity of the user (U) and/or an acceleration of the user (U).
A throttle valve control device comprising a throttle body having an intake passage , the throttle valve control device driving a throttle valve for controlling an intake air flow rate or a pressure, disposed in the intake passage , with a motor via a throttle gear , and the throttle valve control device being attached externally with a bolt inserted into an attachment hole formed in the throttle body , wherein only three attachment holes are formed in the throttle body , one attachment hole among the three attachment holes is formed closer to a center of gravity of the throttle valve control device than the other two attachment holes , and the one attachment hole is formed between the motor and a throttle shaft , characterized in that in a case where the throttle valve control device is divided into first to fourth quadrants in a counterclockwise direction based on a center of the intake passage when the intake passage is viewed in a penetration direction of the intake passage , in case the motor is located on the second and third quadrant side, the three attachment holes are formed in the first quadrant, the third quadrant, and the fourth quadrant, or in case the motor is located on the first and fourth quadrant side, the attachment holes are formed in the second quadrant, the third quadrant and the fourth quadrant, and the motor is disposed in the same quadrant as the one attachment hole .
Gas generator comprising: - at least one pyrotechnic material arranged to produce gases; - at least one sub-assembly formed at least by a first part and a second part that are attached to one another by means of friction welding; - at least one third part that is attached to at least one of the first part and the second part by means of friction welding, the third part and one of the first part and the second part each comprising an indexing interface arranged to temporarily block at least two degrees of freedom between the third part and said one of the first part and the second part , so as to allow simultaneous inertia welding of the third part and said one of the first part and the second part to the other of the first part and the second part , the friction welding being carried out by means of a welding operation using a rotational inertia tool, and characterized in that the indexing interface is arranged to ensure a rotation of the third part by said one of the first part and the second part during the welding operation, without contact between the rotational inertia tool and the third part . - at least one pyrotechnic material arranged to produce gases; - at least one sub-assembly formed at least by a first part and a second part that are attached to one another by means of friction welding; - at least one third part that is attached to at least one of the first part and the second part by means of friction welding,
A compound of Table 1 for use in preventing or treating an inflammatory disease. [Table 1] Compound names Compound structures S02546436 S02276077 S06696686 S06690562 S06713271 S02396152 S01525559 S06542401 S01739292 S01688300 S06570841 S06570001 S06568641 S06572801 S01577528 S01382085 S01442577 S01414289 S01292238
A laundry treatment apparatus comprising: a support body for supporting laundry; an inlet port provided in an upper portion of the support body ; an air supply unit coupled to the inlet port and configured for supplying air downwardly into the laundry hung on the support body ; and a tensile force provision unit separably connected to the support body or to the laundry hung on the support body for providing tensile force to the laundry, and for providing at least some of the air supplied into the laundry to flow back toward the air supply unit , wherein the tensile force provision unit is configured to function as a weight for straightening the laundry and comprises: a tensile force provision body for separating inner circumferential surface parts of the laundry from each other by closing at least a portion of the opening formed in the lower end of the laundry such that the inner circumferential surface parts of the laundry are spaced apart from each other by a predetermined distance. a support body for supporting laundry; an inlet port provided in an upper portion of the support body ; an air supply unit coupled to the inlet port and configured for supplying air downwardly into the laundry hung on the support body ; and a tensile force provision unit separably connected to the support body or to the laundry hung on the support body for providing tensile force to the laundry, and for providing at least some of the air supplied into the laundry to flow back toward the air supply unit , wherein the tensile force provision unit is configured to function as a weight for straightening the laundry and comprises: a tensile force provision body for separating inner circumferential surface parts of the laundry from each other by closing at least a portion of the opening formed in the lower end of the laundry such that the inner circumferential surface parts of the laundry are spaced apart from each other by a predetermined distance.
A combine harvester comprising: a header for harvesting crop material on the ground; a ground speed sensor configured to detect a ground speed of the combine; a ground height sensor configured to detect a contour of the ground located directly beneath the header ; a forward looking sensor (FLS) configured to detect a contour of the ground forward of the header ; and wherein the combine harvester further comprises a controller configured to receive signals from the ground speed sensor , the ground height sensor and the forward looking sensor , characterized in that the controller is further configured to calculate a header height output as a function of (i) an output of the ground speed sensor , which represents a ground speed of the combine, (ii) an output of the ground height sensor , which represents the contour of the ground located directly beneath the header , and (iii) an output of the forward looking sensor , which represents the contour of the ground that is forward of the header , said controller being further configured to weight the outputs of the ground speed sensor and the forward looking sensor as a function of the speed of the combine harvester in calculating the header height output. a header for harvesting crop material on the ground; a ground speed sensor configured to detect a ground speed of the combine; a ground height sensor configured to detect a contour of the ground located directly beneath the header ; a forward looking sensor (FLS) configured to detect a contour of the ground forward of the header ; and wherein the combine harvester further comprises a controller configured to receive signals from the ground speed sensor , the ground height sensor and the forward looking sensor , characterized in that the controller is further configured to calculate a header height output as a function of (i) an output of the ground speed sensor , which represents a ground speed of the combine, (ii) an output of the ground height sensor , which represents the contour of the ground located directly beneath the header , and (iii) an output of the forward looking sensor , which represents the contour of the ground that is forward of the header , said controller being further configured to weight the outputs of the ground speed sensor and the forward looking sensor as a function of the speed of the combine harvester in calculating the header height output.
A conductive silicone composition comprising: a catalyst-type conductive rubber composition containing 100 parts by weight of catalyst-type liquid silicone and 0.5 to 2.5 parts by weight of carbon nanotubes; and a crosslinking-type conductive rubber composition containing 100 parts by weight of crosslinking-type liquid silicone and 0.5 to 2.5 parts by weight of carbon nanotubes, wherein the initial viscosity of each of the catalyst-type liquid silicone and the crosslinking-type liquid silicone is 5,000 to 41,000 CP, the average viscosity of the conductive rubber compositions is 80,000 to 350,000 cP, the viscosity difference between the initial viscosity of the liquid silicones and the average viscosity of the conductive rubber compositions is 70,000 to 310,000, and the viscosity was measured at a temperature of 25°C and a shear rate of 10 s -1 . a catalyst-type conductive rubber composition containing 100 parts by weight of catalyst-type liquid silicone and 0.5 to 2.5 parts by weight of carbon nanotubes; and a crosslinking-type conductive rubber composition containing 100 parts by weight of crosslinking-type liquid silicone and 0.5 to 2.5 parts by weight of carbon nanotubes, wherein the initial viscosity of each of the catalyst-type liquid silicone and the crosslinking-type liquid silicone is 5,000 to 41,000 CP, the average viscosity of the conductive rubber compositions is 80,000 to 350,000 cP, the viscosity difference between the initial viscosity of the liquid silicones and the average viscosity of the conductive rubber compositions is 70,000 to 310,000, and the viscosity was measured at a temperature of 25°C and a shear rate of 10 s -1 .
A peptide consisting of the amino acid sequence of SEQ ID NO: 4 or 5.
A method of representing content elements in associated display windows on a display device of a scale, characterized in that , in the method, - hardware parameters of the display device which influence the representation of the content elements on the display device are read out, - at least one content element is accessed which is to be represented at a respective point in time in a respective display window on the display device and with which respective additional information is associated that at least partly predefines the respective representation, and - the absolute dimensions of the display window associated with the respective content element to be represented are automatically calculated based on the hardware parameters and the respective additional information under the condition of a distortion-free representation of the respective content element on the display device , wherein the absolute dimensions of the respective display window are to be understood as the length of the sides of the respective display window, i.e. the actual extent of the respective display window on the display device. - hardware parameters of the display device which influence the representation of the content elements on the display device are read out, - at least one content element is accessed which is to be represented at a respective point in time in a respective display window on the display device and with which respective additional information is associated that at least partly predefines the respective representation, and - the absolute dimensions of the display window associated with the respective content element to be represented are automatically calculated based on the hardware parameters and the respective additional information under the condition of a distortion-free representation of the respective content element on the display device , wherein the absolute dimensions of the respective display window are to be understood as the length of the sides of the respective display window, i.e. the actual extent of the respective display window on the display device.
A method of managing a virtual network, VN, comprising a plurality of VN members, each VN member comprising a network tunnel traversing one or more physical links through one or more physical network domains, the method comprising: associating one or more of the VN members with a first group, the first group comprising VN members requiring dedicated resource allocations for their corresponding network tunnels; associating one or more others of the VN members with a second group, the second group comprising VN members that may share resource allocations with other VN members of the second group; assigning paths through the one or more physical network domains for the VN members of the first group, such that the assigned paths for the VN members of the first group provide dedicated resource allocations to each VN member of the first group; and assigning paths through the one or more physical network domains for the VN members of the second group, such that at least one pair of VN members of the second group traversing a common physical link share a bandwidth allocation for the common physical link. associating one or more of the VN members with a first group, the first group comprising VN members requiring dedicated resource allocations for their corresponding network tunnels; associating one or more others of the VN members with a second group, the second group comprising VN members that may share resource allocations with other VN members of the second group; assigning paths through the one or more physical network domains for the VN members of the first group, such that the assigned paths for the VN members of the first group provide dedicated resource allocations to each VN member of the first group; and assigning paths through the one or more physical network domains for the VN members of the second group, such that at least one pair of VN members of the second group traversing a common physical link share a bandwidth allocation for the common physical link.
A vehicle control unit , in particular an autonomous driving control unit, comprising: a microcontroller unit ; a sealing controller unit , configured to detect a mechanical change to the housing ; an electrical connector coupling the microcontroller unit to the sealing controller unit ; and a housing enclosing the microcontroller unit , the sealing controller unit and the electrical connector ; characterized in that the sealing controller unit includes a memory means for storing a validity state, wherein the memory means include a memory chip; the microcontroller unit is configured to determine the validity state of the sealing controller unit via the electrical connector and wherein the sealing controller unit is configured to change the validity state when a mechanical change to the housing is detected. a microcontroller unit ; a sealing controller unit , configured to detect a mechanical change to the housing ; an electrical connector coupling the microcontroller unit to the sealing controller unit ; and a housing enclosing the microcontroller unit , the sealing controller unit and the electrical connector ; characterized in that the sealing controller unit includes a memory means for storing a validity state, wherein the memory means include a memory chip; the microcontroller unit is configured to determine the validity state of the sealing controller unit via the electrical connector and wherein the sealing controller unit is configured to change the validity state when a mechanical change to the housing is detected.
A computer-implemented method for identifying an abnormal medical image, the method comprising: receiving a medical image ; segmenting an anatomical structure from the medical image to define a segmented dataset; registering the segmented dataset to a baseline dataset defining a normal anatomical structure; classifying, by an abnormality classifier , whether the anatomical structure within the medical image is either abnormal or normal, wherein the abnormality classifier comprises a machine learning algorithm trained to distinguish between normal and abnormal versions of the anatomical structure in medical images ; and based on whether the anatomical structure can be segmented from the medical image , whether the segmented dataset can be registered to the baseline dataset, and a classification associated with the medical image output by the abnormality classifier , flagging the medical image as either normal or abnormal. receiving a medical image ; segmenting an anatomical structure from the medical image to define a segmented dataset; registering the segmented dataset to a baseline dataset defining a normal anatomical structure; classifying, by an abnormality classifier , whether the anatomical structure within the medical image is either abnormal or normal, wherein the abnormality classifier comprises a machine learning algorithm trained to distinguish between normal and abnormal versions of the anatomical structure in medical images ; and based on whether the anatomical structure can be segmented from the medical image , whether the segmented dataset can be registered to the baseline dataset, and a classification associated with the medical image output by the abnormality classifier , flagging the medical image as either normal or abnormal.