Abstract: Methods and systems for optimizing hydrogen fuel production facilities include processing user input data and sensor data from hardware sensors of a hydrogen fuel production facility with a computerized device to model at least one microgrid hydrogen-generating plant. A three-stage convex optimization model is operated on the computerized device to determine at least one implementation parameter of the microgrid hydrogen-generating plant. At least one hardware component of the microgrid hydrogen-generating plant is modeled. The hardware components include at least an electrolyzer. A model predictive control (MPC) controller is used to determine an optimal power flow schedule for a selected control scenario and schedule module, thereby optimizing the generated sensor data and the user input data over a time series window.

Abstract: The present application discloses novel compounds, and compositions comprising said compounds, that are effective small-molecule agonists that stimulate overproduction of cytosolic cyclic AMP (cAMP) in Mycobacterium tuberculosis (Mtb) which inhibits cholesterol metabolism. These small-molecule agonists demonstrate potentiation of current tuberculosis (TB) therapeutics, exhibiting potential as a promising new class of agents for the treatment of TB. The application further discloses methods of treatment of TB using compositions comprising the disclosed novel compounds in combination therapy with current TB therapeutics.

Abstract: Disclosed herein are compounds and compositions comprising the compounds of Formula I (I) wherein all variables are as defined herein. Further disclosed are methods for using the above compounds and compositions comprising the above compounds for the prevention, amelioration, or treatment of malarial infections alone or in combination with other therapeutic agents, including additional anti-malarial drugs.

Abstract: The present disclosure provides a compound of Formula (I): or a tautomer or pharmaceutically acceptable salt thereof, wherein Rings A, B, C, and R1 and R2 are defined herein, their pharmaceutical compositions, and methods of use for treating diseases that are vulnerable to inhibition of TEAD family transcription factors and/or inhibition of the pro-growth activity of the transcriptional coactivator YAP.

Abstract: A method and system for mobile storage and dispensing of hydrogen (H2) for refueling H2-powered vehicles includes a compressor system having a plurality of compressor stages in fluid communication with at least a portion of manifold valves in locations between compressor stages. A booster compression stage positioned downstream of the compressor system is in fluid communication between at least two of the manifold valves. A plurality of H2 storage banks is positioned downstream of the compressor system and the booster compressor stage. Low-pressure H2 is pressurized by the compressor system and/or the booster compressor stage to a working pressure and stored within the H2 storage banks. Upon a decrease of the H2 in one or more of the H2 storage banks from the working pressure, the H2 is repressurized by the booster compressor stage. Also disclosed is a ground-based cryogenic tank and a method of manufacturing a ground-based cryogenic tank.

Abstract: Disclosed is a system for controlling gaseous hydrogen (GH2) refueling of a GH2 vehicle, wherein a vehicle fuel tank is refilled with GH2 from an external supply tank. The system includes a target patch or a cell of a temperature-dependent reflectivity material on an exterior of the vehicle fuel tank, and a sensor package including an electromagnetic (EM) radiation emitter and a radiation detection system positioned remote from the vehicle tank being filled. The sensor package is located on or adjacent an external refueling device with a line of sight to the target patch or cell.

Abstract: A composition 100 of a sweet corn silk extract 102 for a medicinal use is provided. The composition includes 0.25-0.50 percent weight of Maysin 104, 2.0-3.0 percent weight of natural potassium 106, 7.5-9.0 percent weight of total polyphenols 108, and 1.0-2.0 percent weight of vitamin C 110.

Abstract: Research work in the literature on imputation of mobility data for missing records of a subject's location trajectory has been specifically revolved around usage of historical data. Thus, performances drop when missing records or imputation mobility data for unknown subject with very little or no historical data has to be predicted. A method and system for training an ensemble classifier for imputation of mobility data of unknown subject based on cohort of the unknown subject is disclosed. The method and system disclosed herein exploits the knowledge that semantic trajectories of different individuals has considerable similarity when individuals belong to the same cohort. This concept is used by the method to predict the behavior of all the individuals in a cohort using ensemble classifier, also referred to as imputation model, trained on the semantic location data of a fraction of total individuals in the cohort with a certain accuracy.

Abstract: Provided herein are compounds, compositions, and their methods of use for treatment and/or prevention of infections of HBV in a subject by administering a compound of structural formula (I) or a pharmaceutically acceptable salt thereof: wherein R1 and R2 are defined herein.

Abstract: The present disclosure relates to compounds, and to their pharmaceutical compositions, that inhibit dipeptidyl peptidase IV (DPP4). The compounds selectively promote the proliferation of alveolar type 2 cells (AEC2s) and are useful in therapeutic methods of treating diseases whose etiology, for example, derives from epithelial degeneration and maladaptive remodeling, such as pulmonary diseases like idiopathic pulmonary fibrosis (IPF), acute respiratory distress syndrome (ARDS), and infant respiratory distress syndromes (IRDS).

Abstract: The present disclosure provides compounds, or their tautomers or pharmaceutically acceptable salts thereof, and their pharmaceutical compositions that can selectively activate Yes-associated protein 1 (YAP). YAP activators of the present disclosure are useful in therapies such as wound and organ repair including, for example, treatment of chronic ulcers.

Abstract: Existing systems for behavioural tracking and identification have the disadvantage that they do not analyse data in behavioural aspects. As a result, they lack ability to pre-empt scenarios involving actions that adversely affect user health. The disclosure herein generally relates to behavior prediction, and, more particularly, to a method and system for identifying unhealthy behavior trigger and providing nudges. The system generates a casual inference model, which is a reverse causality model facilitating mapping of context with one or more behaviour of the user. The system further collects and processes real-time data using the casual inference model, to perform behavioral analysis of the user.

Abstract: The present disclosure relates to compounds. and to their pharmaceutical compositions. that inhibit dipeptidyl peptidase IV (DPP4). Hie compounds selectively promote the proliferation of alveolar type 2 cells (AEC2s) and are useful in therapeutic methods of treating diseases whose etiology. for example. derives from epithelial degeneration and maladaptive remodeling, such as pulmonary' diseases like idiopathic pulmonary fibrosis (IFF), acute respiratory' distress syndrome (ARDS), and infant respiratory' distress syndromes (IRDS).

Abstract: A system and method for routing requests to an API to two or more API endpoints are disclosed. The system comprises at least a gateway router and a configuration server. When software is executed, the system transmits, from the configuration server to the gateway router, information setting a desired proportion of API requests to be allocated to each of the two or more API endpoints. When API requests are received, the gateway router forwards the API requests to the API endpoints in the desired proportion. The system receives metrics data from one or more backend entities upon which at least one of the API endpoints relies for data or other services, and determines that an adverse event is underway or imminent based at least in part on the received metrics data. In response to the event, it forwards the API requests in a second proportion different from the desired proportion.

Abstract: This disclosure relates generally to method and system for performing negotiation task using reinforcement learning agents. Performing negotiation on a task is a complex decision making process and to arrive at consensus on contents of a negotiation task is often expensive and time consuming due to the negotiation terms and the negotiation parties involved. The proposed technique trains reinforcement learning agents such as negotiating agent and an opposition agent. These agents are capable of performing the negotiation task on a plurality of clauses to agree on common terms between the agents involved. The system provides modelling of a selector agent on a plurality of behavioral models of a negotiating agent and the opposition agent to negotiate against each other and provides a reward signal based on the performance. This selector agent emulate human behavior provides scalability on selecting an optimal contract proposal during the performance of the negotiation task.

Abstract: Provided herein are compounds, pharmaceutical compositions, and methods for inhibiting the ENL YEATS domain. Further, provided herein are compounds, pharmaceutical compositions, and methods for the treatment of leukemia.

Abstract: In presence of high-cardinality treatment variables, number of counterfactual outcomes to be estimated is much larger than number of factual observations, rendering the problem to be ill-posed. Furthermore, lack of information regarding the confounders among large number of covariates pose challenges in handling confounding bias. Essential is to find lower-dimensional manifold where an equivalent problem of causal inference can be posed, and counterfactual outcomes can be computed.

Abstract: Causality is a crucial paradigm in several domains where observational data is available. Primary goal of Causal Inference (CI) is to uncover cause-effect relationship between entities. Conventional methods face challenges in providing an accurate CI framework due to cofounding and selection bias in multiple treatment scenario. The present disclosure computes a Propensity Score (PS) from a received CI data for the plurality of subjects under test for a treatment. A Generalized Propensity Score (GPS) is computed for a plurality of treatments corresponding to the plurality of subjects by using the PS. Further, a plurality of task batches are created using the GPS and given as input to the DNN for training. Errors in factual data and in balancing representation of the DNN are rectified using a novel loss function. The trained DNN is further used for predicting the counter factual treatment response corresponding to the factual treatment data.

Abstract: A method of geosteering in a wellbore construction process uses an earth model that defines boundaries between formation layers and petrophysical properties of the formation layers in a subterranean formation. Sensor measurements related to the wellbore construction process are inputted to the earth model. An estimate is obtained for a relative geometrical and geological placement of the well path with respect to a geological objective using a trained reinforcement learning agent. An output action based on the sensor measurement for influencing a future profile of the well path with respect to the estimate.

Abstract: This disclosure relates generally to method and system for performing negotiation task using reinforcement learning agents. Performing negotiation on a task is a complex decision making process and to arrive at consensus on contents of a negotiation task is often expensive and time consuming due to the negotiation terms and the negotiation parties involved. The proposed technique trains reinforcement learning agents such as negotiating agent and an opposition agent. These agents are capable of performing the negotiation task on a plurality of clauses to agree on common terms between the agents involved. The system provides modelling of a selector agent on a plurality of behavioral models of a negotiating agent and the opposition agent to negotiate against each other and provides a reward signal based on the performance. This selector agent emulate human behavior provides scalability on selecting an optimal contract proposal during the performance of the negotiation task.