Abstract: A laundry care or dish care composition can include a poly alpha-1,6-glucan derivative, wherein the poly alpha-1,6-glucan derivative includes: (i) a poly alpha-1,6-glucan backbone of glucose monomer units, wherein greater than or equal to 40% of the glucose monomer units are linked via alpha-1,6 glycosidic linkages, and wherein from 0% to less than 30% of the glucose monomer units are linked via alpha-1,3 glycosidic linkages, and optionally at least 5% of the backbone glucose monomer units have branches via alpha-1,2 and/or alpha-1,3 glycosidic linkages; and (ii) at least one organic group linked to the poly alpha-1,6-glucan backbone through a linkage moiety; wherein, the poly alpha-1,6-glucan backbone has a weight average degree of polymerization of at least 5; and wherein, the poly alpha-1,6-glucan derivative has a degree of substitution of linkage moiety of from 0.20 to 1.00.

Abstract: The present invention relates to a reinforcement mesh (1) for use in construction, the mesh (1) comprising a plurality of longitudinally and transversely extending reinforcing members (2), wherein either of the longitudinal or the transverse reinforcing members (2), each comprises a rebar comprising strands (3) of material twisted together, the strands being parted at spaced locations along their length by the other of the longitudinal or transverse rebars which extend through, and are secured at, the spaced locations of the parted strands (4).

Abstract: Techniques for generating dynamic dust emission risk index values via construction and use of a dynamic dust emission risk index model are provided. In one example, a computer-implemented method comprises generating, by a system operatively coupled to a processor, a dynamic dust emission risk index value based on a dynamic dust emission risk index model. The computer implemented method also includes supplying, by the system, the dynamic dust emission risk index value to an air quality model. Additionally, the computer implemented method further comprises generating, by the system, a dust emission forecast based on the air quality model.

Abstract: Post-processing corrections can be applied to operational numerical model forecasts of weather variables to reduce forecast model errors. The post-processing technique is based on an analog post-processing correction scheme. In the analog scheme, the system searches for previous model forecasts that are similar to the current forecast, and modifies the current forecast based on errors in such previous predictions. An “abnormal (or abnormal) index” can be generated for each analog as a function of several meteorology variables (i.e., humidity, pressure and temperature) and two experience coefficients. The abnormal index can be used to exclude some errors. Furthermore, dynamic weights based on the “abnormal index” can be applied to the errors. Using the “abnormal index” weights in a post-processing technique may generate a more accurate air quality forecast.

Abstract: Post-processing corrections can be applied to operational numerical model forecasts of weather variables to reduce forecast model errors. The post-processing technique is based on an analog post-processing correction scheme. In the analog scheme, the system searches for previous model forecasts that are similar to the current forecast, and modifies the current forecast based on errors in such previous predictions. An “abnormal (or abnormal) index” can be generated for each analog as a function of several meteorology variables (i.e., humidity, pressure and temperature) and two experience coefficients. The abnormal index can be used to exclude some errors. Furthermore, dynamic weights based on the “abnormal index” can be applied to the errors. Using the “abnormal index” weights in a post-processing technique may generate a more accurate air quality forecast.

Abstract: A method for establishing and using a pollutant emission scavenging forecasting (PESF) model to calculate a purgeable pollutant emission to dynamically control an emitted pollutant at any target concentration. The dynamic control considers the initial pollutant concentration and pollutant scavenging ability of atmosphere. The method further takes into account the constraint conditions specified by a user, and employs a dynamic emission correction system to quickly calculate an optimal pollutant emission scheme. If the emission is lower than minimum acceptable value for a current time instance (a moment), the method corrects the emission intensity before (prior to) this moment by changing the initial concentration at this time. This initial concentration is the final pollutant concentration of a prior moment. Since the method makes full use of the atmospheric pollutants scavenging ability, the dynamic emission control scheme can provide the most effective and lowest economic losses solution.

Abstract: A system, method and computer program product for establishing and using a pollutant emission scavenging forecasting (PESF) model to calculate a purgeable pollutant emission to dynamically control an emitted pollutant at any target concentration. The dynamic control considers the initial pollutant concentration and pollutant scavenging ability of atmosphere. The method further takes into account the constraint conditions specified by a user, and employs a dynamic emission correction system to quickly calculate an optimal pollutant emission scheme. If the emission is lower than minimum acceptable value for a current time instance (a moment), the method corrects the emission intensity before (prior to) this moment by changing the initial concentration at this time. This initial concentration is the final pollutant concentration of a prior moment.

Abstract: A method is disclosed for designing a test vehicle utilizing a layout of a real integrated circuit (IC) product. The method comprises: importing an original full-chip layout of the real IC product; partitioning the original full-chip layout into probe groups, each probe group comprising probe pads, and, a plurality of IC devices within an area of interest (AOI) having original routing interconnect for those IC devices; selecting a set of IC devices within the AOI; and, for the selected set of IC devices, using pattern extraction to remove the original routing interconnect, and create customized interconnect layers (CIL) to reconfigure connection between the individual IC devices. Incorporating the selected set of IC devices with the CIL into the original full-chip layout creates a modified full-chip layout such that a wafer fabricated using the modified full-chip layout comprises a real product with a built-in test vehicle.

Abstract: According to one or more embodiments of the present invention, a method of forecasting air quality is provided. The method includes determining weather pattern classifications based on global atmospheric information from a global weather model and determining a synoptic scale correction factor in response to the determination of the weather pattern classifications. The method also includes blending the global atmospheric information the synoptic scale correction factor to produce a data set and blending the data set with regional atmospheric information from a regional weather model to generate weather fields. The method further includes blending chemical information from a global chemical model and the synoptic scale correction factor to produce a second data set and blending the second data set into a regional chemical model based on the weather fields to forecast the air quality.

Abstract: Post-processing corrections can be applied to operational numerical model forecasts of weather variables to reduce forecast model errors. The post-processing technique is based on an analog post-processing correction scheme. In the analog scheme, the system searches for previous model forecasts that are similar to the current forecast, and modifies the current forecast based on errors in such previous predictions. An “abnormal (or abnormal) index” can be generated for each analog as a function of several meteorology variables (i.e., humidity, pressure and temperature) and two experience coefficients. The abnormal index can be used to exclude some errors. Furthermore, dynamic weights based on the “abnormal index” can be applied to the errors. Using the “abnormal index” weights in a post-processing technique may generate a more accurate air quality forecast.

Abstract: Post-processing corrections can be applied to operational numerical model forecasts of weather variables to reduce forecast model errors. The post-processing technique is based on an analog post-processing correction scheme. In the analog scheme, the system searches for previous model forecasts that are similar to the current forecast, and modifies the current forecast based on errors in such previous predictions. An “abnormal (or abnormal) index” can be generated for each analog as a function of several meteorology variables (i.e., humidity, pressure and temperature) and two experience coefficients. The abnormal index can be used to exclude some errors. Furthermore, dynamic weights based on the “abnormal index” can be applied to the errors. Using the “abnormal index” weights in a post-processing technique may generate a more accurate air quality forecast.

Abstract: A method for establishing and using a pollutant emission scavenging forecasting (PESF) model to calculate a purgeable pollutant emission to dynamically control an emitted pollutant at any target concentration. The dynamic control considers the initial pollutant concentration and pollutant scavenging ability of atmosphere. The method further takes into account the constraint conditions specified by a user, and employs a dynamic emission correction system to quickly calculate an optimal pollutant emission scheme. If the emission is lower than minimum acceptable value for a current time instance (a moment), the method corrects the emission intensity before (prior to) this moment by changing the initial concentration at this time. This initial concentration is the final pollutant concentration of a prior moment. Since the method makes full use of the atmospheric pollutants scavenging ability, the dynamic emission control scheme can provide the most effective and lowest economic losses solution.

Abstract: A system, method and computer program product for establishing and using a pollutant emission scavenging forecasting (PESF) model to calculate a purgeable pollutant emission to dynamically control an emitted pollutant at any target concentration. The dynamic control considers the initial pollutant concentration and pollutant scavenging ability of atmosphere. The method further takes into account the constraint conditions specified by a user, and employs a dynamic emission correction system to quickly calculate an optimal pollutant emission scheme. If the emission is lower than minimum acceptable value for a current time instance (a moment), the method corrects the emission intensity before (prior to) this moment by changing the initial concentration at this time. This initial concentration is the final pollutant concentration of a prior moment.

Abstract: According to one or more embodiments of the present invention, a method of forecasting air quality is provided. The method includes determining weather pattern classifications based on global atmospheric information from a global weather model and determining a synoptic scale correction factor in response to the determination of the weather pattern classifications. The method also includes blending the global atmospheric information the synoptic scale correction factor to produce a data set and blending the data set with regional atmospheric information from a regional weather model to generate weather fields. The method further includes blending chemical information from a global chemical model and the synoptic scale correction factor to produce a second data set and blending the second data set into a regional chemical model based on the weather fields to forecast the air quality.

Abstract: Techniques for generating dynamic dust emission risk index values via construction and use of a dynamic dust emission risk index model are provided. In one example, a computer-implemented method comprises generating, by a system operatively coupled to a processor, a dynamic dust emission risk index value based on a dynamic dust emission risk index model. The computer implemented method also includes supplying, by the system, the dynamic dust emission risk index value to an air quality model. Additionally, the computer implemented method further comprises generating, by the system, a dust emission forecast based on the air quality model.

Abstract: An extensive apparatus includes a shaft, a sensor, a display, a sleeve and a shell. The sensor is attached to the shaft so that the sensor detects torque exerted on the shaft. The display is electrically connected to the sensor so that the value of the torque detected by the sensor is shown on the display. The sleeve includes a tunnel through which the shaft extends. The sleeve is connected to the shaft so that they can only rotate together. The shell is rotationally provided around the sleeve. The display is connected to the shell so that the display is rotational relative to the shaft and easily observable regardless of the shaft.

Abstract: An extensive apparatus includes a shaft, a sensor, a display, a sleeve and a shell. The sensor is attached to the shaft so that the sensor detects torque exerted on the shaft. The display is electrically connected to the sensor so that the value of the torque detected by the sensor is shown on the display. The sleeve includes a tunnel through which the shaft extends. The sleeve is connected to the shaft so that they can only rotate together. The shell is rotationally provided around the sleeve. The display is connected to the shell so that the display is rotational relative to the shaft and easily observable regardless of the shaft.