Abstract: This application describes examples of a grid-tied inverter apparatus and a grid-tied control method. In one example, the grid-tied inverter apparatus includes an inverter circuit, a controller, and a filter circuit. The controller is configured to adjust switching frequencies of a plurality of power switching transistors based on an output current value of the inverter apparatus, to adjust a resonance frequency of the filter circuit through different resonant branches, so that the resonance frequency meets a grid-tied requirement.

Abstract: Embodiments of this application provide methods and apparatuses for offline payment authorization. In an implementation, a method comprising: obtaining wallet account information, a current account balance, and current credit information of a target electronic wallet account in response to determining that a current state of the target electronic wallet account satisfies a predetermined certificate delivery condition, determining an offline payment limit based on the current account balance and the current credit information, signing summary information by using a private key of a server to obtain an electronic wallet signature, generating a user certificate based on the summary information and the electronic wallet signature, and sending the user certificate to a terminal device associated with the target electronic wallet account for an offline account corresponding to the target electronic wallet account to make offline payment within the offline payment limit based on the user certificate.

Abstract: Provided are methods and compositions from reprogramming human glial cells into human neurons. The reprogramming is achieved using combinations of compounds that can modify signaling via Transforming growth factor beta (TGF-?), Bone morphogenetic protein (BMP), glycogen synthase kinase 3 (GSK-3), and ?-secretase/Notch pathways. The reprogramming is demonstrated using groups of three or four compounds that are chosen from the group thiazovivin, LDN193189, SB431542, TTNPB, CHIR99021, DAPT, VPA, SAG, purmorphamine. Reprogramming is demonstrated using the group of LDN193189/CHIR99021/DAPT, the group of B431542/CHIR99021/DAPT, the group of LDN193189/DAPT/SB431542, the group of LDN193189/CHIR99021/SB431542, a three drug combination of SB431542/CHIR99021/DAPT. Reprogramming using functional analogs of the compounds is also provided, as are pharmaceutical formulations that contain the drug combinations.

Abstract: A reclining foldable chair includes a support frame and a seat cover secured to the support frame. The support frame is configured to transition between a storage and use position and includes a first and second upright, a seat bottom support, a collapsible cross-brace, a seat back rest, and a reclining assembly configured to allow the chair to transition between upright and reclined positions. The reclining assembly includes a recline limiter and a pivoting link latch. The pivoting link latch includes a pivoting link and a moving link, wherein an overall length between opposite ends of the pivoting link and moving link is adjustable in order to transition the reclining foldable chair between the upright and reclined positions.

Abstract: The present invention relates to application of gossypol and its optical isomers to preparation of an anti-Coronavirus drug. Specifically disclosed is application of pharmaceutically acceptable salts, solvates, isotopes, stereoisomers, stereoisomer mixtures, and tautomers of the gossypol and its optical isomers to preparation of a drug for preventing and/or treating a disease caused by a Coronavirus. The Coronavirus is MERS-CoV, SARS-CoV, or SARS-CoV-2. It is found in the present invention for the first time that the gossypol and its optical isomers can inhibit the activity of Coronavirus 3CL proteases to achieve an anti-Coronavirus effect. The half maximal inhibitory concentrations of gossypol and (?)-gossypol to SARS-CoV proteases and SARS-CoV-2 3CL proteases are all lower than 10 ?M. The anti-Coronavirus 3CL protease effect is good. Therefore, the gossypol and its optical isomers have the potential for use in the preparation of a drug for preventing and/or treating novel Coronavirus infections.

Abstract: An example microscope includes a pump laser for providing a first illumination to a sample. A laser array provides a second illumination to the sample. The laser array may include a plurality of laser elements, each providing oblique illuminations to the sample. An illumination collecting source collects the first illumination and the second illumination from the sample. The illumination collecting source may capture transient 3D refractive index (RI) variations in the sample due to the first illumination and second illumination.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data, and in particular mass spectrometry data obtained by data-independent acquisition. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. To sequence peptides from mass spectrometry data obtained by data-independent acquisition, precursor profiles representing intensities of one or more precursor ion signals associated with a precursor retention time and fragment ion spectra representing signals from fragment ions and fragment retention times are fed into a neural network.

Abstract: The present systems and methods are directed to de novo identification of peptide sequences from tandem mass spectrometry data. The systems and methods uses unconverted mass spectrometry data from which features are extracted. Using unconverted mass spectrometry data reduces the loss of information and provides more accurate sequencing of peptides. The systems and methods combine deep learning and neural networks to sequencing of peptides.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.

Abstract: A pencil sharpener having a flexible storage cover, comprising a pencil sharpener main body portion (2). The main body portion (2) comprises a base (22) and a blade (26) accommodated in the base (22). The blade (26) is provided with an insertion hole for insertion of a pencil. The base (22) is provided with a base portion (23). The top of the base portion (23) is provided with at least one hole (2312) corresponding to the insertion hole. The pencil sharpener further comprises a flexible storage portion (3) that can be bonded to the base portion (23) or detached from the base portion (23) and used for storing pencil debris. The flexible storage portion (3) comprises a fixing portion (31) and a flexible storage cover (33) bonded to the fixing portion (31). The fixing portion (31) can be bonded to or detached from the base portion (23).

Abstract: A pencil sharpener having a flexible storage cover, comprising a pencil sharpener main body portion (2). The main body portion (2) comprises a base (22) and a blade (26) accommodated in the base (22). The blade (26) is provided with an insertion hole for insertion of a pencil. The base (22) is provided with a base portion (23). The top of the base portion (23) is provided with at least one hole (2312) corresponding to the insertion hole. The pencil sharpener further comprises a flexible storage portion (3) that can be bonded to the base portion (23) or detached from the base portion (23) and used for storing pencil debris. The flexible storage portion (3) comprises a fixing portion (31) and a flexible storage cover (33) bonded to the fixing portion (31). The fixing portion (31) can be bonded to or detached from the base portion (23).

Abstract: The present systems and methods are directed to de novo identification of peptide sequences from tandem mass spectrometry data. The systems and methods uses unconverted mass spectrometry data from which features are extracted. Using unconverted mass spectrometry data reduces the loss of information and provides more accurate sequencing of peptides. The systems and methods combine deep learning and neural networks to sequencing of peptides.

Abstract: The present systems and workflows identify neoantigens for cancer immunotherapy by introducing deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and workflow allows for patient specific identification of neoantigens for personalized immunotherapy.

Abstract: Methods and systems for determining amino acid sequence of a polypeptide or protein from mass spectrometry data is provided, using a weighted de Bruijn graph. Extracted and purified protein is cleaved into a mixture of peptide and then analyzed using mass spectrometry. A list of peptide sequences is derived from mass spectrometry fragment data by de novo sequencing, and amino acid confidence scores are determined from peak fragment ion intensity. A weighted de Bruijn graph is constructed for the list of peptide sequences having node weights defined by k?1 mer confidence scores. At least one contig is assembled from the de Bruijn graph by identifying node weights having the highest k?1 mer confidence scores.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data, and in particular mass spectrometry data obtained by data-independent acquisition. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. To sequence peptides from mass spectrometry data obtained by data-independent acquisition, precursor profiles representing intensities of one or more precursor ion signals associated with a precursor retention time and fragment ion spectra representing signals from fragment ions and fragment retention times are fed into a neural network.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.