Abstract: Provided are a surfactant adhesive protein comprising an amphiphilic peptide, as a surfactant adhesive protein, at the carbon or amine terminal, a silicone oil and an anticancer composition comprising the surfactant adhesive, where the surfactant adhesive enables homogeneous dispersion of hydrophilic or hydrophobic particles in a hydrophobic or hydrophilic solvent on the basis of strong adhesive strength of the mussel adhesive protein, and the surface adhesive can be favorably used as a surface coating agent requiring antibacterial or antiviral functions as well as a cosmetic product or an ink.

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Abstract: A method for detecting defects in a semiconductor device includes pre-training a pre-trained convolutional neural network (CNN) model using a sampled clean data set extracted from a first data set; training a normal convolutional neural network model and a label-noise convolutional neural network model using first data of the first data set and the pre-trained convolutional neural network model. The method also includes outputting a first prediction result on whether second data of a second data set is good or bad using the second data and the normal convolutional neural network model; and outputting a second prediction result on whether second data is good or bad using the second data and the label-noise convolutional neural network model. The first prediction result is compared with the second prediction result to perform noise correction when there is a label difference. Third data created as results of the noise correction is added to the sampled clean data set.

Abstract: The present invention relates to an antibody specifically binding to a tryptophanyl-tRNA synthetase (WRS) protein and, more specifically, to: an antibody, or a fragment of the antibody, specifically binding to a polypeptide of an amino acid sequence represented by SEQ ID NO: 2 in a WRS protein; a polynucleotide encoding the antibody and a vector comprising same; a cell transformed using same; and a use thereof.

Abstract: The present invention relates to an antibody specifically binding to a WRS (tryptophanyl-tRNA synthetase) protein, and a use thereof. More specifically, the present invention pertains to an antibody specifically binding to a polypeptide of an amino acid sequence represented by SEQ ID NO:2 in the WRS (tryptophanyl-tRNA synthetase) protein, or a fragment of the antibody, a polynucleotide encoding the antibody, a vector comprising the polynucleotide, a cell transformed using the vector, and a use of the cell.

Abstract: The present invention relates to a colorectal cancer diagnostic composition and method for detecting a diagnostic marker, more specifically to a colorectal cancer diagnostic composition comprising one or more mRNAs selected from the group consisting of lysyl-tRNA synthetase (KRS) and aminoacyl-tRNA synthetase complex-interacting multifunctional protein 1 (AIMP1) of a preparation for measuring protein expression levels thereof, and a method for detecting a marker form a sample obtained from a test subject in order to provide information necessary for diagnosing colorectal cancer. The colorectal cancer diagnostic marker comprising KRS and AIMP1, according to the present invention, has raised expression levels of same in the serum of a colorectal cancer patient in comparison to a normal control group. Therefore, whether colorectal cancer is present can be accurately and rapidly determined by measuring the expression levels of one or more markers selected from the group consisting of KRS and AIMP1.

Abstract: The present invention relates to novel fragments of AIMP1 protein and a composition for improving alopecia and promoting hair growth comprising the same, more specifically it relates to a polypeptide consisting of 4 to 21 consecutive amino acids from the amino acid sequence of SEQ ID NO: 1, wherein the polypeptide comprises the 28th to 31st amino acid residue (KEKA) of amino acid sequence of SEQ ID NO: 1, or a polypeptide consisting of an amino acid sequence having 70% or more sequence homology with the polypeptide; a polynucleotide encoding the polypeptide; a pharmaceutical, cosmetic and food composition for improving alopecia and promoting hair growth comprising the polypeptide.

Abstract: A user wears a virtual reality mask (VR mask) (100) and then watches a virtual reality image. The VR mask (100) blocks light incident from the outside. When the user wears the VR mask (100), the user cannot discover an obstacle (500) positioned outside the VR mask (100). The user may collide with the obstacle (500) and may be injured by the obstacle (500). Accordingly, in order to prevent injury to the user who uses the VR mask (100), it is necessary to make the user recognize the obstacle (500) positioned outside the VR mask (100). In order to recognize an obstacle, a virtual reality image and the obstacle may be displayed together, or the amount of light incident from the outside may be adjusted.

Abstract: The present invention relates to novel fragments of AIMP1 protein and a composition for improving alopecia and promoting hair growth comprising the same, more specifically it relates to a polypeptide consisting of 4 to 21 consecutive amino acids from the amino acid sequence of SEQ ID NO: 1, wherein the polypeptide comprises the 28th to 31st amino acid residue (KEKA) of amino acid sequence of SEQ ID NO: 1, or a polypeptide consisting of an amino acid sequence having 70% or more sequence homology with the polypeptide; a polynucleotide encoding the polypeptide; a pharmaceutical, cosmetic and food composition for improving alopecia and promoting hair growth comprising the polypeptide.

Abstract: A user wears a virtual reality mask (VR mask) (100) and then watches a virtual reality image. The VR mask (100) blocks light incident from the outside. When the user wears the VR mask (100), the user cannot discover an obstacle (500) positioned outside the VR mask (100). The user may collide with the obstacle (500) and may be injured by the obstacle (500). Accordingly, in order to prevent injury to the user who uses the VR mask (100), it is necessary to make the user recognize the obstacle (500) positioned outside the VR mask (100). In order to recognize an obstacle, a virtual reality image and the obstacle may be displayed together, or the amount of light incident from the outside may be adjusted.

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Abstract: Provided are a surfactant adhesive protein comprising an amphiphilic peptide, as a surfactant adhesive protein, at the carbon or amine terminal, a silicone oil and an anticancer composition comprising the surfactant adhesive, where the surfactant adhesive enables homogeneous dispersion of hydrophilic or hydrophobic particles in a hydrophobic or hydrophilic solvent on the basis of strong adhesive strength of the mussel adhesive protein, and the surface adhesive can be favorably used as a surface coating agent requiring antibacterial or antiviral functions as well as a cosmetic product or an ink.

Abstract: Described are methods and devices for enrichment and in situ expansion of circulating tumor cells (CTCs) from biological samples. The methods may include detecting at least one or more of cell adhesion molecules as epithelial mesenchymal transition (EMT) biomarker. Also described is device for detecting or enriching CTCs. The surface of the device may provide at least one or more of cell binding ligands such as ECM or cadherin derived peptide motif to detect the EMT biomarker. Also described is a surface to remove leukocytes from biological samples, leading to efficient enrichment of CTCs from the biological samples.

Abstract: Fragments of ARS-interacting multi-functional protein 1 (AIMP1) protein and a composition comprising the same as an active ingredient for preventing skin-aging, anti-wrinkle, and improving skin flexibility or elasticity are described.

Abstract: A particle separation apparatus, according to an embodiment of the present invention, may comprise: a first input flow path into which a first fluid containing a plurality of particles of different sizes is introduced; a second input flow path into which a second fluid not containing particles is introduced; a connection flow path and the second input flow path so that a third fluid in which the first fluid and the second fluid are mixed movies; a plurality of discharge flow paths where the plurality of particles which come out through the other end of the connection flow path are separated and discharged according to the size of the particles; and a branch flow path where at least a part of the third fluid which comes out through the other end of the connection flow path is discharged.

Abstract: A semiconductor wafer fault analysis system includes: a database to store a first reference map, which is classified as a first fault type, and a second reference map, which is classified as a second fault type; a first auto-encoder/decoder to remove a noise corresponding to the first fault type from the first reference map to generate a first pre-processed reference map; a second auto-encoder/decoder to remove a noise corresponding to the second fault type from the second reference map to generate a second pre-processed reference map; and a fault type analyzer. The database is updated based on the first and second pre-processed reference maps, and the fault type analyzer is to classify a fault type of a target map based on the updated database. The target map is generated by measuring a target wafer.

Abstract: A fault analysis method of a semiconductor fault analysis device is provided. The fault analysis method includes: receiving measurement data measured corresponding to a semiconductor device; generating double sampling data based on the measurement data and reference data; performing a fault analysis operation with respect to the double sampling data; classifying a fault type of the semiconductor device based on a result of the fault analysis operation; and outputting information about the fault type.

Abstract: A polypeptide having chemokine activity mediated by binding to C-C chemokine receptor type 3 (CCR3) comprising SEQ ID NO: 1 and uses thereof are described.

Abstract: The present invention relates to novel fragments of AIMP1 protein and a composition for improving alopecia and promoting hair growth comprising the same, more specifically it relates to a polypeptide consisting of 4 to 21 consecutive amino acids from the amino acid sequence of SEQ ID NO: 1, wherein the polypeptide comprises the 28th to 31st amino acid residue (KEKA) of amino acid sequence of SEQ ID NO: 1, or a polypeptide consisting of an amino acid sequence having 70% or more sequence homology with the polypeptide; a polynucleotide encoding the polypeptide; a pharmaceutical, cosmetic and food composition for improving alopecia and promoting hair growth comprising the polypeptide.

Abstract: A method for detecting defects in a semiconductor device includes pre-training a pre-trained convolutional neural network (CNN) model using a sampled clean data set extracted from a first data set; training a normal convolutional neural network model and a label-noise convolutional neural network model using first data of the first data set and the pre-trained convolutional neural network model. The method also includes outputting a first prediction result on whether second data of a second data set is good or bad using the second data and the normal convolutional neural network model; and outputting a second prediction result on whether second data is good or bad using the second data and the label-noise convolutional neural network model. The first prediction result is compared with the second prediction result to perform noise correction when there is a label difference. Third data created as results of the noise correction is added to the sampled clean data set.