Abstract: A machine learning method predicts whether a specified subject is at high risk of developing cognitive impairment based upon a data record for said specified subject, and a method of training a dual neural network for such. These methods may work by automatically classifying said subject into a first class associated with a first predicted risk of cognitive impairment or a second class associated with a second predicted risk of cognitive impairment. Subject records are obtained comprising a first set of measured data and a second set of data including results for two or more health assessment questionnaires; and a label indicating that the subject belongs to the first class or second class. These records are used to train first and second neural networks, and in the latter method these trained networks are able to predict whether a specified subject should belong to said first class or second class.

Abstract: A combined testbench type and walking type compliant exoskeleton system quickly and efficiently converts from a fixed testbench configuration to a mobile orthosis configuration. The addition of a series elastic actuator allows the combined testbench type and walking type compliant exoskeleton system to have a higher level of safe physical human-robot interaction and safety for users with spasticity or tremor. Alternate embodiments incorporating a combination of the rigid and compliant joints, allowing the combination of a swing test and enhancement of a user's strength for walking or other movement is also disclosed.

Abstract: A non-invasive liquid detection method based on acoustic wave features and an apparatus thereof, the method includes: collecting acoustic waves penetrating a liquid to be tested and extracting acoustic absorption-transmission curve features from the acoustic waves to generate a liquid fingerprint, the acoustic absorption-transmission curve features represent a ratio of an energy of an acoustic signal penetrating the liquid to an energy of an acoustic signal emitted across a plurality of frequencies; inputting the liquid fingerprint into a trained neural network model for detection processing, and outputting detection results. The neural network model is trained with a plurality of sets of data, and each set of data includes: acoustic absorption-transmission curve features, and a label identifying a feature that meets a detection requirement in the acoustic absorption-transmission curve features.

Abstract: An algorithm-driven digital ultraviolet (UV) lithography (DUL) method and apparatus used to fabricate high-quality optical waveguide and many other kinds of high-resolution microstructures without the use of a photomask. Instead of the use of an actual photomask, a virtual mask based on a spatial light modulator is used. The DUL method and apparatus can compensate for a proximity effect caused by light scattering and make the exposure adaptive to a nonlinear response curve of a photoresist, in which an exposure dose-map is created based on the bitmap of a designed pattern together with the optimization parameters determined by system configuration and the photoresist. To fabricate large-area patterns, a plurality of sliced exposure dose-submaps with transition zones that can depress the stitching error caused by mechanical mispositioning are generated for digital lithographic exposure process.

Abstract: A woven, water-vapor permeable, water-responsive, shape-memory wool fabric that possesses switchable pore size and shape responsive to varying water content absorbed thereby is demonstrated, more particularly, the wool fabric exerts corresponding thermal and water vapor regulations between the wearer and the surroundings with respect to the temperature and humidity changes.

Abstract: The present disclosure provides a bracewear for spinal correction and a system for posture training. The system for posture training involves both active and passive corrective forces by using the bracewear and a biofeedback system to address the spinal correction, which can eliminate the adversity of conventional hard braces and reduce the psychological and physiological barriers to treatment.

Abstract: Embodiments of the present disclosure provide a fuel cell power generation device, which includes: a fuel cell with an anode and a cathode, for decomposing hydrogen and generating electric energy through reaction of decomposed hydrogen and oxygen; a first delivery pipe connected between a pipeline of a hydrogen-containing gas and the fuel cell, for delivering the hydrogen-containing gas to the anode of the fuel cell; a first output pipe connected to the fuel cell, for discharging a first remaining gas contacted with the anode of the fuel cell; a second delivery pipe connected to the fuel cell, for delivering an oxygen-containing gas to the cathode of the fuel cell; and a second output pipe connected to the fuel cell, for discharging a second remaining gas contacted with the cathode of the fuel cell.

Abstract: A method of preparing antimicrobial 3D-printed material with antimicrobial agents integrated with the 3D-printed material. The 3D-printed material fabricated with the method of the present disclosure includes antimicrobial agent (s) fully integrated throughout the product and display antimicrobial effect throughout the product, which is resistant to daily wear and tear.

Abstract: A method and an apparatus for sending key-value pair data are provided, and a method and an apparatus for collecting key-value pair data are provided. In the method, first target key-value pair data is perturbed as first perturbed key-value pair data, so that a data collector can determine, based on a value a or b of a first value in the first perturbed key-value pair data, whether to include the entire first perturbed key-value pair data into the statistical result in a process of generating the statistical result. In this way, an association between a value and a key in the key-value pair data is reserved in the first perturbed key-value pair data, which improves availability of the first perturbed key-value pair data. That is, a statistical result generated by the data collector based on the first perturbed key-value pair data is closer to a statistical result generated based on original user key-value pair data.

Abstract: The present disclosure describes a system, method and software applications for predicting the KAM of a subject for a plurality of gait cycles of a subject. At least one sensor attachable adjacent to the ankle of at least one leg of the subject provides accelerometer and gyroscopic data for the plurality of gait cycles. A processing means receives subject parameters and accelerometer and gyroscopic data from the at least one sensor for evaluation by a neural network of predicted KAM values for the plurality of gait cycles of the subject. The neural network is configured via determining KAM values for each of the plurality of subjects from measurements during a plurality of gait cycles and other parameters.

Abstract: This invention relates to compounds of formula 1, 2 or 3 a pharmaceutically acceptable salt, or solvate thereof, wherein X1, Y, R1, R2, R3, R4, and R5 are as defined herein. The compounds are antimicrobial agents that may be used to treat various bacterial and protozoal infections and disorders related to such infections. The invention also relates to pharmaceutical compositions containing the compounds and to methods of treating bacterial and protozoal infections by administering the compounds of formula 1, 2 or 3.

Abstract: A machine learning method predicts whether a specified subject is at high risk of developing cognitive impairment based upon a data record for said specified subject, and a method of training a dual neural network for such. These methods may work by automatically classifying said subject into a first class associated with a first predicted risk of cognitive impairment or a second class associated with a second predicted risk of cognitive impairment. Subject records are obtained comprising a first set of measured data and a second set of data including results for two or more health assessment questionnaires; and a label indicating that the subject belongs to the first class or second class. These records are used to train first and second neural networks, and in the latter method these trained networks are able to predict whether a specified subject should belong to said first class or second class.

Abstract: This disclosure provides a biodegradable antimicrobial material based on polylactic acid oligomer represented by formula 1 as an active ingredient. The disclosure also provides a process for preparing the polylactic acid oligomer and an antimicrobial product prepared therefrom.

Abstract: The present disclosure relates to a surface comprising a photocatalyst affixed thereupon via an adhesive layer and methods for affixing the photocatalyst to the surface via the adhesive layer. The present disclosure also provides a purifier comprising the photocatalyst affixed surface and a purifier system comprising such purifier.

Abstract: Aberrant cross talk between Notch ligand (e.g. Jag1) and Notch receptor (e.g. Notch1) has been implicated in tumorigenesis in the colon. Inhibition of Notch pathway is therefore an attractive approach for treating diseases with upregulated Jag1 e.g. colorectal cancer (CRC). Pan-notch inhibitors like gamma secretase inhibitors (GSIs) have been developed to inhibit Notch and its downstream events. However, severe gastrointestinal toxicity profiles impede the clinical development of GSIs. The present invention develops novel oligopeptides that specifically inhibit Jag1-Notch1 pathway without interfering DLL1-Notch1 or DLL4-Notch1, which demonstrates a clear advantage over pan-notch inhibitors.

Abstract: A yarn twisting method and device for a ring spinning machine is provided. The twisting method comprises the following steps: feeding three roving strands (1, 2, 3) into a back roller (8) of the ring spinning machine; after drafting, the three roving strands, three fiber strands (1, 2, 3) exiting from a nip point of a front roller (10), wherein a fiber strand (2) in the middle forms an angle with a plane formed by the other two fiber strands (1, 3), and thus the three fiber strands (1, 2, 3) form a multi-strand spinning triangle region having a three-dimensional spatial form; and in the multi-strand spinning triangle region, the three fiber strands (1, 2, 3) obtaining twist by means of a ring traveler of the ring spinning machine, and the twisted fiber strands (1 ,2, 3) are combined into a composite yarn (4) through a convergence point.

Abstract: Method of treating endometriosis and related indications, comprising the administration of Pro-EGCG, a synthetic and derivative product of epigallocatechin-3-gallate [(?)-EGCG]. Use of PRO-EGCG in the manufacture of a medicament for treating endometriosis and related indications. Pro-EGCG for use in the treatment of endometriosis and related indications.

Abstract: A multi-level-architecture multi-fiber composite yarn includes a composite yarn having a first anisotropic expansion coefficient in an axial and/or radial direction, and a matrix material included with the yarn, wherein the matrix material has a second anisotropic expansion coefficient that is different from the first anisotropic expansion coefficient in at least one of the axial or radial directions. A method of fabricating a multi-level-architecture multi-fiber composite yarn includes infiltrating a composite yarn having a first anisotropic expansion coefficient in an axial and/or radial directions with a matrix material having a second anisotropic expansion coefficient different from the first anisotropic expansion coefficient in the axial or radial direction.

Abstract: The present disclosure provides a method and system for analysing one or more edible oil samples. In an embodiment the disclosure provides for calibrating the matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) data obtained for one or more edible oil samples to obtain calibrated spectral data; and comparing the calibrated spectral data derived from the one or more samples against a library of calibrated MALDI-MS spectra for a plurality of edible oil samples to determine the most likely composition of the one or more edible oil samples.

Abstract: The present disclosure provides a cesium tungsten bronze-based self-cleaning nano heat-insulation coating material, and method of preparing the same. Cesium tungsten bronze nanoparticles are prepared by hydrothermal method using WCl6 and CsOH.5H2O as raw materials, PVP as a surfactant and acetic acid as an acid catalyst. TiO2 nanoparticles are prepared from TiCl4. Subsequently ball milling and dispersing of the cesium tungsten bronze nanoparticles, the TiO2 nanoparticles, and a silane coupling agent with water to obtain an aqueous slurry containing cesium tungsten bronze/TiO2 composite particles is performed. The concentration of the aqueous slurry containing cesium tungsten bronze/TiO2 composite particles is adjusted to obtain a self-cleaning nano heat-insulation coating material.