Abstract: A valve includes a first plate having a first vent hole; a second plate defining a valve chamber, which communicates with the first vent hole, between the second plate and the first plate, the second plate having a second vent hole that communicates with the valve chamber and that does not face the first vent hole; and a movable plate having a third vent hole that faces the second vent hole and disposed in the valve chamber such that the movable plate is movable between the first plate and the second plate. The second plate has an auxiliary hole that does not face the third vent hole in the movable plate, the auxiliary hole being surrounded by an edge portion that forms a first corner portion having a substantially convex rounded shape in front view of a principal surface of the second plate at a side facing the valve chamber.

Abstract: A failure analysis device 10 is provided with an identification unit 11 that discriminates whether a predetermined failure has occurred on the basis of a learning model for discriminating the presence or absence of an occurrence of the predetermined failure learned by using a cause attribute which is associated with a cause of the predetermined failure and on the basis of a value of the attribute, and that identifies the cause of the predetermined failure discriminated to have occurred and countermeasures therefor.

Abstract: An object of the present disclosure is to provide a control apparatus that controls a plurality of communication systems so that the plurality of communication systems can perform analysis with high accuracy. The control apparatus (30) according to the present disclosure includes a communication unit (31) and a determination unit (32). The communication unit (31) receives, from an analysis apparatus (10) configured to perform machine learning using communication logs collected from a communication apparatus in order to generate a learning model, statistical information about each of the communication logs and information about the learning model. The determination unit (32) determines an analysis apparatus (20) to which the information about the learning model is applied based on the statistical information.

Abstract: A first prediction unit 83 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration in a communication section between one communication device and another communication device communicably connected to the one communication device by using a first learning model generated on the basis of first attributes being attributes related to a cause of communication quality deterioration in the communication section. A second prediction unit 84 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration outside the communication section regarding one communication device by using a second learning model generated on the basis of second attributes being attributes related to a cause of communication quality deterioration outside the communication section regarding the one communication device.

Abstract: An object of the present disclosure is to provide a control apparatus that controls a plurality of communication systems so that the plurality of communication systems can perform analysis with high accuracy. The control apparatus (30) according to the present disclosure includes a communication unit (31) and a determination unit (32). The communication unit (31) receives, from an analysis apparatus (10) configured to perform machine learning using communication logs collected from a communication apparatus in order to generate a learning model, statistical information about each of the communication logs and information about the learning model. The determination unit (32) determines an analysis apparatus (20) to which the information about the learning model is applied based on the statistical information.

Abstract: A first prediction unit 83 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration in a communication section between one communication device and another communication device communicably connected to the one communication device by using a first learning model generated on the basis of first attributes being attributes related to a cause of communication quality deterioration in the communication section. A second prediction unit 84 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration outside the communication section regarding one communication device by using a second learning model generated on the basis of second attributes being attributes related to a cause of communication quality deterioration outside the communication section regarding the one communication device.

Abstract: A failure analysis device 10 is provided with an identification unit 11 that discriminates whether a predetermined failure has occurred on the basis of a learning model for discriminating the presence or absence of an occurrence of the predetermined failure learned by using a cause attribute which is associated with a cause of the predetermined failure and on the basis of a value of the attribute, and that identifies the cause of the predetermined failure discriminated to have occurred and countermeasures therefor.

Abstract: An object of the present disclosure is to provide an analysis apparatus capable of solving a problem that the amount of data processing increases and the processing load thus increases. An analysis apparatus (10) according to the present disclosure includes: a prediction unit (13) configured to perform machine learning using past traffic data in a communication system to thereby predict future traffic data in the communication system; an analysis unit (11) configured to analyze the future traffic data using first input data and generate a first analysis result corresponding to a first purpose; and an analysis unit (12) configured to analyze the future traffic data using second input data and generate a second analysis result corresponding to a second purpose.

Abstract: A coated base fabric for an airbag has a fabric composed of polyamide fibers provided with a resin coating, wherein the polyamide fibers which compose the base fabric have a total fineness of not less than 100 dtex and not more than 250 dtex and a tenacity of not less than 8.1 cN/dtex and the coated base fabric has a basis weight of not more than 170 g/m2, packability of the base fabric in accordance with ASTM D6478-02 of not more than 1,400 cm3, a tear strength in a warp direction and a weft direction of not less than 200 N and an edgecomb resistance in the warp direction and the weft direction of not less than 200 N.

Abstract: An airbag base fabric satisfying characteristics A to D: (A) the cross-sectional deformation (WR), calculated by formula (1), of multifilament warp threads constituting a textile is 4.0 to 6.0, WR=(Major axis of warp thread cross section in textile)/(Minor axis of warp thread cross section in textile)??(1) (B) the cross-sectional deformation (FR), calculated by formula (2), of multifilament weft threads constituting the textile is 2.4 to 4.0, FR=(Major axis of weft thread cross section in textile)/(Minor axis of weft thread cross section in textile)??(2) (C) the single fiber cross-sectional shape of the multifilament threads constituting the textile is substantially circular, and (D) the multifilament threads constituting the textile have total fineness of 145 to 720 dtex, single fiber fineness of 2 to 7 dtex, and tensile strength of 6.5 to 8.5 cN/dtex.

Abstract: An airbag base fabric having a warp direction energy absorption characteristic defined by formula (1) is 30 to 50 and a weft direction energy absorption characteristic defined by formula (2) is 30 to 50: Warp Direction Energy Absorption Characteristic=Warp Direction Energy Absorption Amount/Warp Yarn Cover Factor??(1) wherein the warp direction energy absorption amount is a value of integral of stress applied, in measurement of the warp direction tensile strength and elongation at break, from a start of the measurement until the sample breaks; and Weft Direction Energy Absorption Characteristic=Weft Direction Energy Absorption Amount/Weft Yarn Cover Factor??(2) wherein the weft direction energy absorption amount is a value of the integral of stress applied, in measurement of the weft direction tensile strength and elongation at break, from the start of the measurement until the sample breaks.

Abstract: An airbag base fabric having a warp direction energy absorption characteristic defined by formula (1) is 30 to 50 and a weft direction energy absorption characteristic defined by formula (2) is 30 to 50: Warp Direction Energy Absorption Characteristic=Warp Direction Energy Absorption Amount/Warp Yarn Cover Factor??(1) wherein the warp direction energy absorption amount is a value of integral of stress applied, in measurement of the warp direction tensile strength and elongation at break, from a start of the measurement until the sample breaks; and Weft Direction Energy Absorption Characteristic=Weft Direction Energy Absorption Amount/Weft Yarn Cover Factor??(2) wherein the weft direction energy absorption amount is a value of the integral of stress applied, in measurement of the weft direction tensile strength and elongation at break, from the start of the measurement until the sample breaks.

Abstract: A coated base fabric for an airbag has a fabric composed of polyamide fibers provided with a resin coating, wherein the polyamide fibers which compose the base fabric have a total fineness of not less than 100 dtex and not more than 250 dtex and a tenacity of not less than 8.1 cN/dtex and the coated base fabric has a basis weight of not more than 170 g/m2, packability of the base fabric in accordance with ASTM D6478-02 of not more than 1,400 cm3, a tear strength in a warp direction and a weft direction of not less than 200 N and an edgecomb resistance in the warp direction and the weft direction of not less than 200 N.

Abstract: An airbag base fabric satisfying characteristics A to D: (A) the cross-sectional deformation (WR), calculated by formula (1), of multifilament warp threads constituting a textile is 4.0 to 6.0, WR=(Major axis of warp thread cross section in textile)/(Minor axis of warp thread cross section in textile) ??(1) (B) the cross-sectional deformation (FR), calculated by formula (2), of multifilament weft threads constituting the textile is 2.4 to 4.0, FR=(Major axis of weft thread cross section in textile)/(Minor axis of weft thread cross section in textile) ??(2) (C) the single fiber cross-sectional shape of the multifilament threads constituting the textile is substantially circular, and (D) the multifilament threads constituting the textile have total fineness of 145 to 720 dtex, single fiber fineness of 2 to 7 dtex, and tensile strength of 6.5 to 8.5 cN/dtex.

Abstract: An airbag fabric, airbag and method for making the airbag fabric, the fabric consisting of warp and weft yarns of synthetic fiber yarn, characterized by satisfying the following requirements: (1) the total fineness of the synthetic fiber yarn is 100 to 700 dtex; (2) Nf/Nw?1.10 wherein, Nw represents the weaving density of warp yarns (yarns/2.54 cm) and Nf represents the weaving density of weft yarns (yarns/2.54 cm); (3) EC1?400N and EC2?400N wherein, EC1 represents the edgecomb resistance (N) in the machine direction, as determined according to ASTM D6479-02, and EC2 represents the edgecomb resistance (N) in the crosswise direction as determined according to ASTM D6479-02; (4) 0.85?EC2/EC1?1.15; and (5) the air permeability, as determined according to the Frajour type method specified in JIS L1096 at a test pressure difference of 19.6 kPa, is 1.0 L/cm2·min or less.

Abstract: A yarn for air bags including polyamide multifilament with a total fineness of 200 to 700 dtex, a single fiber fineness of 1 to 2 dtex, strength of 7 to 10 cN/dtex, and elongation of 20 to 30%.

Abstract: An air bag fabric includes a warp and a weft, each including polyamide multifilaments with a total fineness of 200 to 700 dtex and a single fiber fineness of 1 to 2 dtex and having a cover factor (CF) of 1,800 to 2,300, wherein a ratio ECw/Mtw between edgecomb resistance, EDw, and single fiber fineness, Mtw, in the warp direction, and a ratio ECf/Mtf between edgecomb resistance, ECf, and single fiber fineness, Mtf, in the weft direction are both in a range of 250 to 1,000 N/dtex.

Abstract: A composition for promoting root nodule formation, which can be easily applied to soil or plants, and enables efficient formation of root nodules, and a method for promoting root nodule formation using the composition are provided. A composition for promoting root nodule formation, which comprises a compound selected from the group consisting of a nucleoside, a nucleotide, and a nucleobase such as inosine, as an active ingredient, is applied to a leguminous plant to promote root nodule formation of the plant.

Abstract: An air bag fabric includes a warp and a weft, each including polyamide multifilaments with a total fineness of 200 to 700 dtex and a single fiber fineness of 1 to 2 dtex and having a cover factor (CF) of 1,800 to 2,300, wherein a ratio ECw/Mtw between edgecomb resistance, EDw, and single fiber fineness, Mtw, in the warp direction, and a ratio ECf/Mtf between edgecomb resistance, ECf, and single fiber fineness, Mtf, in the weft direction are both in a range of 250 to 1,000 N/dtex.

Abstract: A microscope apparatus including a light source device, a storage table, and a setting controller is provided. The light source device includes a light intensity adjuster which changes light intensity of an illumination light of plural different wavelength regions selectively extracted from light emitted from a light source, and thereby emitting the illumination light including light of the plural different wavelength regions in such a manner that a light intensity ratio of light of one wavelength region to light of another wavelength region is variable. The storage table stores therein set values of the light intensity adjuster for each of combination patterns of the wavelength regions of the illumination light emitted from the light source device.