Abstract: Some embodiments include apparatuses and electrical models associated with the apparatus. One of the apparatuses includes an integrated circuit having a die; a package substrate; first conductive connections coupled between the die and a first side of the package substrate; second conductive connections located on a second side of the package substrate opposite from the first side. The second conductive connections are coupled to the first conductive connections through conductive paths in the package substrate. The first conductive connections and the conductive connections are associated with an S-parameter of an electrical model of the integrated circuit package. The electrical model further includes at least one of a current value associated with a power rail of the integrated circuit package, an impedance target associated with a location at the integrated circuit package, and a mapping associated with the first and second conductive connections.

Abstract: A computing power network node evaluation and operation method includes: determining overall computing power information of a computing power network; evaluating a computing power service for a computing power service demand based on the overall computing power information and the computing power service demand so as to obtain a computing power evaluation value of each computing power node; determining a computing power configuration scheme corresponding to the computing power service demand based on the computing power evaluation value of each computing power node and a computing power calling mode of each computing power node within a time period corresponding to the computing power service demand; and respectively sending computing power operation instructions to a computing power demand node and a computer power service node indicated in the computing power configuration scheme to establish a computing power calling connection, thus completing the computing power service demand.

Abstract: A computing power distribution method and apparatus, and a computing power server.

Abstract: Provides in the present disclosure are a touch module, a preparation method therefor, and a display device. The touch module is formed by means of attaching a polarizing function layer to a side of a touch function layer by a first bonding layer; attaching a cyclo olefin polymer (COP) film layer to another side of the touch function layer by a second bonding layer; and attaching a third bonding layer to a side, facing away from the second bonding layer, of the COP film layer.

Abstract: Among other things, the disclosure of the present invention is related to make pathology and cytology faster, better, and lower cost, as well as to using fast cytology to quickly determine the concentration of the analyte outside a cell in a sample. The present invention is also related to rapid intra-cellular assays.

Abstract: A method for extracting text relevant to a particular topic from a document to generate a narrower, condensed, more specific, and smaller version obtains information as to the text of a large document and searches the text information of the document based on first keywords to extract first pages. The first pages are inputted into a predetermined learning model to extract second keywords from the first pages, and the first keywords and the second keywords are integrated to obtain third keywords. The method further searches the text of the first pages based on the third keywords to extract second pages and a determination is made as to whether the second pages meet a predetermined page standard. If yes, the second pages are integrated and output. An electronic device and a non-transitory storage medium are also disclosed.

Abstract: Systems, methods, and other embodiments for ML-Based automated below-the-line threshold tuning include, in one embodiment, training an ML model to predict probabilities that an event is fraudulent on a set of events (i) sampled from a set of historic events labeled by an alerting engine as either above-the-line events or below-the-line events on either side of a threshold line indicating that an event is suspicious, and (ii) confirmed to be either fraudulent or not fraudulent; determining that the alerting engine should be tuned based on differences between probability values predicted for the events by the trained machine learning model and the labels applied to the events; generating a tuned threshold value for the threshold line based at least in part on the probability values predicted by the machine learning model; and tuning the alerting engine by replacing a threshold value with the tuned threshold value to adjust the threshold line.

Abstract: Provides in the present disclosure are a touch module, a preparation method therefor, and a display device. The touch module is formed by means of attaching a polarizing function layer to a side of a touch function layer by a first bonding layer; attaching a cyclo olefin polymer (COP) film layer to another side of the touch function layer by a second bonding layer; and attaching a third bonding layer to a side, facing away from the second bonding layer, of the COP film layer.

Abstract: A polymer pre-laid waterproof rolling material, including a polymer base material layer, a pressure-sensitive adhesive layer on the polymer base material layer, and a sand anti-sticking layer on the pressure-sensitive adhesive layer; the pressure-sensitive adhesive layer includes: 25-35 parts by mass of a styrene-isoprene-styrene block copolymer; 32-38 parts by mass of a C5 petroleum resin; 5-12 parts by mass of a 145 pentaerythritol modified rosin resin; 25-32 parts by mass of a naphthenic oil; 0.3 parts by mass of an antioxidant; and 0.5 parts by mass of a UV light stabilizer; the C5 petroleum resin has a softening point of 95-105° C. and a color number of less than 4; the naphthenic oil has a kinematic viscosity of 9-11 mm2 at 100° C. and a density of 0.8950 g/cm3-0.9100 g/cm3 at 20° C. The pressure-sensitive adhesive layer has a stronger bonding effect with sintered sand and further improves the bonding effect with concrete.

Abstract: The disclosure herein discloses a general method for the synthesis of FeCoNiCu-based high-entropy alloy and their application for electrocatalytic water splitting, belonging to the technical field of preparation of composite materials. The catalytic material for electrolysis of water includes a reaction active material and a support. The reaction active material is FeCoNiCu-based high-entropy alloy nanoparticles such as FeCoNiCuSn, FeCoNiCuMn, FeCoNiCuV or the like. The support is a carbon nanofiber material prepared by electrospinning. The catalytic material for electrolysis of water prepared in the disclosure herein has a high specific surface area, which facilitates diffusion of the electrolyte and desorption of gas. By using the catalytic material for electrolysis of water, hydrogen and oxygen can be produced under alkaline conditions, and the hydrogen production rate under high voltage is much higher than that of a 20% Pt/C electrode.

Abstract: Some embodiments include apparatuses and electrical models associated with the apparatus. One of the apparatuses includes an integrated circuit having a die; a package substrate; first conductive connections coupled between the die and a first side of the package substrate; second conductive connections located on a second side of the package substrate opposite from the first side. The second conductive connections are coupled to the first conductive connections through conductive paths in the package substrate. The first conductive connections and the conductive connections are associated with an S-parameter of an electrical model of the integrated circuit package. The electrical model further includes at least one of a current value associated with a power rail of the integrated circuit package, an impedance target associated with a location at the integrated circuit package, and a mapping associated with the first and second conductive connections.

Abstract: Systems, methods, and other embodiments for ML-Based automated below-the-line threshold tuning include, in one embodiment, training an ML model to predict probabilities that an event is fraudulent on a set of events (i) sampled from a set of historic events labeled by an alerting engine as either above-the-line events or below-the-line events on either side of a threshold line indicating that an event is suspicious, and (ii) confirmed to be either fraudulent or not fraudulent; determining that the alerting engine should be tuned based on differences between probability values predicted for the events by the trained machine learning model and the labels applied to the events; generating a tuned threshold value for the threshold line based at least in part on the probability values predicted by the machine learning model; and tuning the alerting engine by replacing a threshold value with the tuned threshold value to adjust the threshold line.

Abstract: The present disclosure discloses a method for preparing cellulose fiber. The method includes the following steps: 1) mixing cellulose pulp with NMMO aqueous solution of a mass concentration of 60%-85%, preferably 70% to 76%, to obtain a uniform mixture; 2) subjecting the obtained uniform mixture to dewatering for swelling, dissolution, and deaerating to obtain a cellulose spinning stock solution; 3) the cellulose spinning stock solution entering into a spinning machine after being filtered and heat exchange, and entering into a coagulation system after carrying out extruding by a spinneret-pack and cooling by air, and then coagulating in a NMMO coagulating bath of a mass concentration of 50% to 72% to obtain nascent fiber; and 4) subjecting the nascent fiber to rinsing to obtain a fiber filament bundle, and then, performing subsequent-section treatment to obtain cellulose fiber.

Abstract: Systems, methods, and other embodiments associated with applying machine learning to below-the-line threshold tuning are described. In one embodiment, a method includes selecting a set of sampled events and labeling each event in the set of sampled events as either suspicious or not suspicious. Then, a machine learning model to calculate for a given event a probability that the given event is suspicious is built based on the set of sampled events. The machine learning model is trained, and its calibration validated. Based on probabilities calculated by the machine learning model, a scenario and segment combination to be tuned is determined. A tuned threshold value is generated, and an alerting engine is adjusted with the tuned parameter to reduce errors by the alerting engine in classifying events as not suspicious.

Abstract: A polymer pre-laid waterproof rolling material, comprising a polymer base material layer, a pressure-sensitive adhesive layer on the polymer base material layer, and a sand anti-sticking layer on the pressure-sensitive adhesive layer; the pressure-sensitive adhesive layer includes: 25-35 parts by mass of a styrene-isoprene-styrene block copolymer; 32-38 parts by mass of a C5 petroleum resin; 5-12 parts by mass of a 145 pentaerythritol modified rosin resin; 25-32 parts by mass of a naphthenic oil; 0.3 parts by mass of an antioxidant; and 0.5 parts by mass of a UV light stabilizer; the C5 petroleum resin has a softening point of 95-105° C. and a color number of less than 4; the naphthenic oil has a kinematic viscosity of 9-11 mm2 at 100° C. and a density of 0.8950 g/cm3-0.9100 g/cm3 at 20° C. The pressure-sensitive adhesive layer has a stronger bonding effect with sintered sand and further improves the bonding effect with concrete.

Abstract: A pre-laid polymer waterproof rolling material, which comprises a sheet-like polymer carrier, a hot-melt pressure-sensitive adhesive layer on the sheet-like polymer carrier, and an anti-sticking coating on the hot-melt pressure-sensitive adhesive layer; The anti-sticking coating comprises the following components: 100-160 parts by weight of water; 50-80 parts by weight of a polyurethane resin; 15-20 parts by weight of a pigment; 10-12 parts by weight of a filler; 0.3-1 part by weight of a cross-linking agent; 0.5-1 part by weight of an antioxidant; 1-2.5 parts by weight of an anti-ultraviolet agent; and 0.03-0.2 part by weight of a thickener. The anti-sticking coating in the present application uses water as a solvent, water is non-toxic and non-corrosive, thus there is no environmental pollution problem in the production process.

Abstract: A pre-laid polymer waterproof rolling material, which comprises a sheet-like polymer carrier, a hot-melt pressure-sensitive adhesive layer on the sheet-like polymer carrier, and a plurality of anti-sticking particles on the hot-melt pressure-sensitive adhesive layer, wherein the particle size of the anti-sticking particles is smaller than the thickness of the hot-melt pressure-sensitive adhesive layer; the surface of the anti-sticking particles is coated with an organic layer; and the anti-sticking particles are connected with the hot-melt pressure-sensitive adhesive layer by means of the organic layer; the organic layer comprises the following components: a solvent, a polyurethane resin, a pigment, a filler, a cross-linking agent, an antioxidant, an anti-ultraviolet agent and a thickener.