Abstract: An integrated circuit layout is provided. The integrated circuit layout includes one or more first cell rows partially extending across a space arranged for an integrated circuit layout along a first direction. Each of the one or more first cell rows has a first height along a second direction perpendicular to the first direction. The integrated circuit layout includes one or more third cell rows partially extending across the space along the first direction. Each of the one or more third cell rows has a second height along the second direction, the second height different from the first height.

Abstract: The present invention belongs to the field of computer visual detection, and relates to a binocular automatic gear pitting detection device based on deep learning, comprising a gearbox system, a data acquisition system, an image processing system, a tooth surface positioning system, a control system and a motor, wherein the gearbox is used for installing paired meshing gears; the data acquisition system is arranged on the side wall of the gearbox, and a CCD industrial camera is arranged on the data acquisition system; the image processing system completes quantitative evaluation of gear pitting and target detection based on a deep learning technology; both ends of the tooth surface positioning system are respectively connected with the motor and the gearbox, and the torque of the motor is transmitted to an input shaft of the gearbox.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: The present disclosure provides a method for predicting a remaining useful life (RUL) of an aero-engine, specifically including: acquiring multidimensional degradation parameters of an aero-engine to be predicted to obtain acquired data; segmenting the acquired data by a sliding window (SW) to obtain preprocessed data; constructing a RUL prediction model of the aero-engine including a multibranch convolutional neural network (MBCNN) model, a multicellular bidirectional long short-term memory (MCBLSTM) model, a fully connected (FC) layer FC1, and a regression layer; taking the preprocessed data as input data of the MBCNN model, extracting an output of the MBCNN model, taking the output of the MBCNN model and recursive data as input data of the MCBLSTM model, and extracting an output of the MCBLSTM model; obtaining an output of the FC layer FC1, and inputting the output of the FC layer FC1 to the regression layer to predict a RUL.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: A computing device having a front-facing camera applies facial landmark detection and identifies eye regions in the digital image responsive to the front-facing camera capturing a digital image of an individual. For at least one of the eye regions, the computing device is further configured to extract attributes of the eye region, determine an eye gaze score based on the extracted attributes, generate a modified eye region based on the eye gaze score, and output a modified digital image with the modified eye region.

Abstract: The present disclosure relates to a composition for preventing and treating Mycoplasma synoviae infection, the composition comprising Tuf, NOX, MS53-0285 or a combination thereof as active ingredients. The composition of the present disclosure is effective in alleviating symptoms caused by Mycoplasma synoviae infection and can be used as an effective tool in preventing or treating poultry diseases.

Abstract: The present disclosure relates to a composition for preventing and treating Mycoplasma synoviae infection, the composition comprising Tuf, NOX, MS53-0285 or a combination thereof as active ingredients. The composition of the present disclosure is effective in alleviating symptoms caused by Mycoplasma synoviae infection and can be used as an effective tool in preventing or treating poultry diseases.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: The present invention belongs to the field of computer visual detection, and relates to a binocular automatic gear pitting detection device based on deep learning, comprising a gearbox system, a data acquisition system, an image processing system, a tooth surface positioning system, a control system and a motor, wherein the gearbox is used for installing paired meshing gears; the data acquisition system is arranged on the side wall of the gearbox, and a CCD industrial camera is arranged on the data acquisition system; the image processing system completes quantitative evaluation of gear pitting and target detection based on a deep learning technology; both ends of the tooth surface positioning system are respectively connected with the motor and the gearbox, and the torque of the motor is transmitted to an input shaft of the gearbox.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: A computing device having a front-facing camera applies facial landmark detection and identifies eye regions in the digital image responsive to the front-facing camera capturing a digital image of an individual. For at least one of the eye regions, the computing device is further configured to extract attributes of the eye region, determine an eye gaze score based on the extracted attributes, generate a modified eye region based on the eye gaze score, and output a modified digital image with the modified eye region.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: A method for predicting a remaining useful life of a lithium battery based on a wavelet denoising and a relevance vector machine, relating to a method for estimating health condition and predicting remaining useful life of lithium battery, includes steps of: (1) obtaining health condition data of each of charge-discharge cycles of the lithium battery by measurement; (2) processing capacity data measured of the lithium battery with wavelet double denoising; (3) calculating a capacity threshold where the lithium battery fails; (4) referring to capacity data and charge-discharge cycle data of the lithium battery, applying a differential evolution algorithm for optimizing a width factor of the relevance vector machine; and (5) predicting the remaining useful life of the lithium battery with the relevance vector machine optimized by the differential evolution algorithm. The method is simple and effective, which can accurately predict remaining useful life of lithium battery.

Abstract: The invention is concerned with compounds, pharmaceutical compositions, screening methods, and therapeutic methods for preventing or reducing a human immunodeficiency virus type-1 (HIV-1) infection and/or propagation associated with dendritic cell immunoreceptor (DCIR). Described herein are compounds which bind on at least one three-dimensional cavity of the DCIR, the cavity(ies) being involved in the interaction between HIV-1 and DCIR. Also described are screening methods for identifying active inhibitors and method of using such inhibitors for the prevention or treatment of virus infections, and more particularly for reducing human immunodeficiency virus type-1 (HIV-1) binding, entry and/or replication in human cells.

Abstract: A method for predicting a remaining useful life of a lithium battery based on a wavelet denoising and a relevance vector machine, relating to a method for estimating health condition and predicting remaining useful life of lithium battery, includes steps of: (1) obtaining health condition data of each of charge-discharge cycles of the lithium battery by measurement; (2) processing capacity data measured of the lithium battery with wavelet double denoising; (3) calculating a capacity threshold where the lithium battery fails; (4) referring to capacity data and charge-discharge cycle data of the lithium battery, applying a differential evolution algorithm for optimizing a width factor of the relevance vector machine; and (5) predicting the remaining useful life of the lithium battery with the relevance vector machine optimized by the differential evolution algorithm. The method is simple and effective, which can accurately predict remaining useful life of lithium battery.

Abstract: A quantum evolution method includes steps of: according to the quantum evolution method, initializing a generation number t=0, and initializing a population Q(t)={q1t, q2t, . . . , qnt}; observing Q(t) and generating P(t)={x 1t, x2t, . . . , xnt}, wherein represents strings comprising 0 or 1 with a length of m; evaluating each xit with an evaluation function, and inputting evaluating results into a fitness function F(t), F(t)={f1t, f2t. . . , fnt}, wherein fit represents a fitness of each individual; selecting an elite group E(t) from P(t) according to the fitness; evolving Q(t) through U(??ijt); inputting an optimal solution b of P(t) into B(t), wherein if the optimal solution is better than an original optimal solution in B(t), then replacing the original optimal solution; otherwise remaining the original optimal solution; and judging a shutdown condition, if satisfied, outputting the optimal solution; otherwise returning to the step (2) for further evolution.