Abstract: A building photovoltaic data interpolation method based on WGAN and whale optimization algorithm is provided, which includes: obtaining historical building roof photovoltaic output data, perform preprocessing on the historical building roof photovoltaic output data, and uses CNN to build a GAN; describing missing value position of preprocessed data by using a binary mask matrix, and setting Wasserstein distance to define a loss function of a GAN generator and a discriminator; taking the loss function as a fitness function, optimizing an input to the GAN generator through a whale optimization algorithm and obtaining optimized candidate samples; fusing the optimized candidate samples and a photovoltaic data processed by the binary mask matrix to obtain completed reconstructed samples, so as to improve the complementary accuracy, optimize the random noise, remove the unfavorable influencing components, and provide services for building rooftop PV data interpolation more accurately.

Abstract: Disclosed are a polyethylene glycol conjugate drug, and a preparation method therefor and the use thereof. Specifically, the present invention relates to a polyethylene glycol conjugate drug represented by formula A or a pharmaceutically acceptable salt thereof, a method for preparing the polyethylene glycol conjugate drug or the pharmaceutically acceptable salt thereof, an intermediate for preparing the polyethylene glycol conjugate drug or the pharmaceutically acceptable salt thereof, a pharmaceutical composition comprising the polyethylene glycol conjugate drug or the pharmaceutically acceptable salt thereof, and the use of the polyethylene glycol conjugate drug or the pharmaceutically acceptable salt thereof in the preparation of a drug.

Abstract: A method for manufacturing and packaging a special-shaped cigarette includes the following steps: designing inner packaging case paper capable of being folded into a special-shaped cigarette accommodating cavity; folding the inner packaging case paper to form the special-shaped cigarette accommodating cavity; filling an interior of the special-shaped cigarette accommodating cavity with an ordinary cigarette; and shelving for a certain period of time, so that a cross section of the ordinary cigarette changes from a circle to a special shape, and the ordinary cigarette is accommodated in the special-shaped cigarette accommodating cavity. A diameter of an inscribed circle of the special-shaped cigarette accommodating cavity is less than a diameter of the ordinary cigarette, and a material of the inner packaging case paper is a paperboard or a food grade PVC sheet.

Abstract: A method for manufacturing and packaging a special-shaped cigarette includes the following steps: designing inner packaging case paper capable of being folded into a special-shaped cigarette accommodating cavity; folding the inner packaging case paper to form the special-shaped cigarette accommodating cavity; filling an interior of the special-shaped cigarette accommodating cavity with an ordinary cigarette; and shelving for a certain period of time, so that a cross section of the ordinary cigarette changes from a circle to a special shape, and the ordinary cigarette is accommodated in the special-shaped cigarette accommodating cavity. A diameter of an inscribed circle of the special-shaped cigarette accommodating cavity is less than a diameter of the ordinary cigarette, and a material of the inner packaging case paper is a paperboard or a food grade PVC sheet.

Abstract: Compositions and methods are provided for simple, instrument-free and sensitive methods that enable rapid, point-of-care detection of nucleic acid molecules of interest. This is based on a surprising discovery that the relative efficiencies of amplification and CRISPR-based cleavage and detection can be tuned to favor amplification until sufficient amplified products are generated to enable detection. Example approaches include design of guide RNA and primers to target nonoptimal PAM sequences, or sequence-engineering Cas nucleases to reduce activities informing a ribonucleoprotein with the guide RNA or binding to or cleaving the substrate nucleic acid.

Abstract: A system and method for identifying a subject using imaging are provided. In some aspects, the method includes receiving an image depicting a subject to be identified, and applying a trained Disentangled Representation learning-Generative Adversarial Network (DR-GAN) to the image to generate an identity representation of the subject, wherein the DR-GAN comprises a discriminator and a generator having at least one of an encoder and a decoder. The method also includes identifying the subject using the identity representation, and generating a report indicative of the subject identified.

Abstract: The invention provides a force stimulation loading device and a working method thereof, the force stimulation loading device comprises: a containing body, a stretching mechanism and a twisting mechanism; the containing body is suitable for containing a gel encapsulating cardiomyocytes, and is made of a non-rigid material; the stretching mechanism is suitable for stretching or squeezing the containing body from opposite sides of the containing body to apply a stretching or squeezing force to the gel; the twisting mechanism is suitable for twisting the containing body to apply a twisting stress to the gel; the force stimulation loading device of the present invention is capable of simultaneously applying the stretching or squeezing force and the twisting stress to the gel encapsulating the cardiomyocytes through the stretching mechanism and the twisting mechanism, that is, applying the stretching or squeezing force and the twisting stress to the cardiomyocytes at the same time.

Abstract: Gait, the walking pattern of individuals, is one of the most important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as the gait features. These methods suffer from degraded recognition performance when handling confounding variables, such as clothing, carrying and view angle. To remedy this issue, a novel AutoEncoder framework is presented to explicitly disentangle pose and appearance features from RGB imagery and a long short-term memory integration of pose features over time produces the gait feature.

Abstract: Gait, the walking pattern of individuals, is one of the most important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as the gait features. These methods suffer from degraded recognition performance when handling confounding variables, such as clothing, carrying and view angle. To remedy this issue, a novel AutoEncoder framework is presented to explicitly disentangle pose and appearance features from RGB imagery and a long short-term memory integration of pose features over time produces the gait feature.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A system and method for identifying a subject using imaging are provided. In some aspects, the method includes receiving an image depicting a subject to be identified, and applying a trained Disentangled Representation learning-Generative Adversarial Network (DR-GAN) to the image to generate an identity representation of the subject, wherein the DR-GAN comprises a discriminator and a generator having at least one of an encoder and a decoder. The method also includes identifying the subject using the identity representation, and generating a report indicative of the subject identified.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.

Abstract: One embodiment of the communication system includes a switch, at least one base station, and a backhaul connection including at least one wireless link connecting the at least one base station to the switch. The wireless link may include at least one of a WiMax carrier and a WiFi carrier.

Abstract: One embodiment of the communication system includes a switch, at least one base station, and a backhaul connection including at least one wireless link connecting the at least one base station to the switch. The wireless link may include at least one of a WiMax carrier and a WiFi carrier.