Abstract: Methods for treating tumors by administering FLASH radiation and a therapeutic agent to a patient with cancer are disclosed. The methods provide the dual benefits of anti-tumor efficacy plus normal tissue protection when combining therapeutic agents with FLASH radiation to treat cancer patients. The methods described herein also allow for the classification of patients into groups for receiving optimized radiation treatment in combination with a therapeutic agent based on patient-specific biomarker signatures. Also provided are radiation treatment planning methods and systems incorporating FLASH radiation and therapeutic agents.

Abstract: This application relates to apparatus and methods for automatically grouping the same or similar items provided by various suppliers that may use various supplier identification systems to identify the items to a retailer. In some examples, item update data identifying an attribute of an item is received and an anomaly is detected in a hierarchical structure of a database. The anomaly is detected by a machine learning model trained by a supervised training dataset based on attributes of items. A hierarchical association between the attribute of the item and the item in the database is generated when the detected anomaly includes a difference between a first hierarchical relationship defined in the item update data and a second hierarchical relationship defined for the item in the database. Item data including the hierarchical association is transmitted to update at least one marketplace.

Abstract: Event management system and method. Events comprise physical and logical attributes. Tuples are created to identify a set of logical attributes. The tuples are arranged in hierarchized relations by creating binarized co-occurrence matrices, each co-occurrence matrix reflecting different time intervals and indicate occurrence of tuples in time windows of the time intervals. Tuple pairs are analyzed to determine probabilistic score related to co-occurrence, and tuple families are created from tuple pairs based on the probabilistic score. From tuple families, events are used to extract tuple instances including physical attributes, which are arranged as tuple-instance families using the corresponding tuple families as reference.

Abstract: The invention provides compositions and methods for treating conditions associated with decreased activity of hydrogen sulfide.

Abstract: A system and method for target material retrieval and processing, the system comprising: an adaptor configured to interface with a capture region of a capture substrate for capturing particles in single-particle format within a set of wells, wherein the adaptor comprises a first region configured to interface with the capture region, a second region, and a cavity extending from the first region to the second region; and a support structure coupled to the adaptor and providing a set of operation modes for movement of the adaptor relative to the capture substrate. The system enables methods for magnetic and/or other force-based methods of retrieval of target material (e.g., derived from single cells).

Abstract: Described herein is a rotor blade assembly (100) and a method for generating a lift in a fluid installation. The rotor blade assembly includes an arcuate rotor blade (102) that is configured to be rotated about its axis Y. One or more motion transmitting members (106, 114, 116) are provided that connect the arcuate rotor blade with at least one power generating member (104) for transmitting torque from the arcuate rotor blade to the at least one power generating member (104). The fluid incident on the arcuate rotor blade is caused to flow over a first leading edge L1 of a rotor blade towards a central rib R of the rotor blade (102). This fluid flow is then caused to flow along the central rib R of the rotor blade towards a stem section of the rotor blade from where the fluid exits, thereby causing rotation of the rotor blade.

Abstract: According to various embodiments described herein, a microfluidics-chip based purification device and system for Sanger-sequencing reactions is provided. The device and system allow for the introduction into a sequencing system of a cartridge containing purification technologies specific to the sequencing contaminants or sequencing method where the simplified purification solution of a cartridge allows automation of the sample purification process, reduced consumption of purification reagents, and consistency in sampling by reducing the sampling errors and artifacts. These various embodiments therefore solve the need for a microfluidics-chip-based, Sanger-sequencing reaction purification system for CE devices. The microfluidic chips described can be used as a PCR chip by reorganizing the on-chip reagents, reaction wells and work flow steps.

Abstract: This disclosure provides a machine learning technique to predict a protein characteristic. A first training set is created that includes, for multiple proteins, a target feature, protein sequences, and other information about the proteins. A first machine learning model is trained and then used to identify which of the features are relevant as determined by feature importance or causal relationships to the target feature. A second training set is created with only the relevant features. Embeddings generated from the protein sequences are also added to the second training set. The second training set is used to train a second machine learning model. The first and second machine learning models may be any type of regressors. Once trained, the second machine learning model is used to predict a value for the target feature for an uncharacterized protein. The model of this disclosure provides 91% accuracy in predicting an ideal digestibility score.

Abstract: The present invention discloses a Double Metal Cyanide (DMC) catalyst(s) useful for the production of polyether polyols (PEPO) and a less energy intensive room temperature method for the synthesis thereof. The catalyst(s) comprises of a DMC complex, an organic complexing agent, i.e., ethylenediaminetetraacetic acid (EDTA) and other co-complexing organic agents, e.g., t-BuOH, PEPO of composition ranging from about 1 to 10 wt %, wherein the average molecular weight of PEPO used ranged from 200 to 1000. A method of preparing a series of DMC catalyst(s) at room temperature with varying compositional ratios of the complexing and co-complexing agents targeting a wide range of PEPO of varying kinematic viscosity range is also disclosed. These DMC catalyst(s) are amorphous, highly active, and easily separable from product PEPO with recyclability/recoverability, making the product PEPO better industrially applicable and DMC catalyst more cost-effective.

Abstract: This disclosure provides a data-driven and scalable method to discover cause-and-effect relationships in data from natural systems that include sparse data sets. This technique can learn a causal graph from heterogenous data sources by combining embeddings from real data and embeddings from simulated data generated by process-based models. The causal graph is used for what-if analysis in out-of-distribution settings. One application is understanding the factors that affect soil carbon. A causal model created by these techniques can be used to discover cause-and-effect relationships that affect soil carbon. This model has applications such as forecasting soil carbon for a future time point to help inform farm practices. Farm practices, like tilling, may be modified in response to predictions provided by the model.

Abstract: A computerized-method for authorizing time-off for a skill to increase agents digital availability is provided herein. The computerized-method includes receiving an agent skill-based time-off request having one or more skills and a duration from a User Interface (UI) in a computerized-device of an agent, and for each skill of the one or more skills in the agent skill-based time-off request: (a) operating an agent-skill-based time-off module to calculate au agent time-off eligibility-quotient.

Abstract: A method, computer program product, and computing system for processing a plurality of input/output (IO) operations on a plurality of storage objects of a storage system. The plurality of storage objects may be divided into a plurality of storage object groups based upon, at least in part, the plurality of IO operations processed on the plurality of storage objects. Each storage object group may be associated with an IO machine learning model selected from a plurality of IO machine learning models, thus defining a plurality of storage object group-specific IO machine learning models. IO performance data may be forecasted for the plurality of storage objects using the plurality of storage object group-specific IO machine learning models.

Abstract: A method includes obtaining, from a plurality of first devices in a first time zone, data associated with hot-prefixes requested at one or more first devices of the plurality of first devices during a first time interval. The hot-prefixes are associated with network addresses that are frequently requested during the first time interval. The method further includes predicting, based on the data associated with the hot-prefixes, prefixes that will become hot-prefixes during a second time interval in a second time zone to determine predicted hot-prefixes, and transmitting an indication of the predicted hot-prefixes to a plurality of second devices configured to provide networking services in the second time zone prior to a start of the second time interval in the second time zone.

Abstract: Disclosed herein are biodegradable polymers, a process to produce polyamines and alkoxylated polyamines, formulations and compositions including polyamines and alkoxylated polyamines, and a method of using polyamines and alkoxylated polyamines as ingredients in formulations and compositions within the field of application of fabric and home care, industrial and institutional cleaning, cosmetics, personal care, agricultural formulations, technical formulations and construction formulations.

Abstract: A method for targeted advertisement includes transmitting a pre-filter to the user device, responsive to contextual information from a user device, to determine, using a processor, one or more inferences based on physical browsing information, collected at the user device, in compliance with one or more privacy policies of the user. The method also includes receiving one or more inferences determined by the pre-filter from the user device and transmitting one or more targeted advertisements to the user device based on one or more inferences.

Abstract: A computer-implemented method is disclosed. The method includes causing display, in a graphical user interface on a client device, of a page with a navigational panel including a selectable tree element having a hierarchical relationship to a current electronic page having its user-generated content being displayed in a content panel. The method includes identifying a set of candidate cards in which each card is associated with a respective electronic page and has a respective relatedness score. The method includes identifying a user profile in accordance with an authentication of an user operating the client device, and selecting, from the set of candidate cards, a subset of candidate cards satisfying permissions criteria based on permissions identified in the user profile. The method includes causing display of the subset of candidate cards within the content panel in accordance with the respective relatedness score for each card in the subset of candidate cards.

Abstract: This application relates to apparatus and methods for automatically grouping the same or similar items provided by various suppliers that may use various supplier identification systems to identify the items to a retailer. In some examples, a computing device receives a supplier identifier from a supplier. The supplier identifier identifies an item that the supplier provides to the retailer for sale. The computing device may determine a group identifier for the item, where the group identifier identifies the item within a group of the retailer. The computing device may update the supplier identifier's association to the retailer identifier based on whether the group identifier is also associated with the retailer identifier. In some examples, the computing device executes a machine learning model to determine anomalies within a current database of supplier identifiers and associated retailer identifiers. In some examples, the computing device indicates changes to associations and any detected anomalies.

Abstract: This disclosure relates method and system for systematic disposal and dynamic procurement of recyclable waste resin. Typical systems for disposal and procurement of recyclable resin pose challenges such as lack of segregation and collection of different types of plastics, data on recycling centers in proximity, uncertainty over resin identification codes, and so on. The disclosed system provides a framework having multiple smart collection units that may be communicatively coupled with a server. The smart bins are capable of collecting plastic items and taking multiple images thereof. The system determines information on type, weight, and location of the plastic resin in the plastic item by means of a trained CNN model, and stores in a repository. The system further includes a route optimization model that is enables selection of a set of collection units for procurement of the resin (of a specific type and a specific quantity).

Abstract: Techniques of scheduling workload(s) on partitioned resources of host systems are described. The techniques can be used, for example, in a container-orchestration system. One technique includes retrieving information characterizing at least one schedulable partition and determining an availability and a suitability of one or more of the schedulable partition(s) for executing a workload in view of the information. Each of the schedulable partition(s) includes resources of one or more host systems. The technique also includes selecting one or more of the schedulable partition(s) to execute the workload in view of the availability and the suitability.

Abstract: Techniques for forecasting temperatures of storage objects in a storage system using machine learning (ML). The techniques can include forecasting at least one temperature of a storage object using at least one ML model, modifying storage of the storage object based on the at least one temperature of the storage object, and, having modified storage of the storage object, obtaining at least one performance metric associated with the storage object. The techniques can further include, based on the performance metric(s), varying a frequency of forecasting the at least one temperature of the storage object, retraining the at least one ML model used in forecasting the at least one temperature, and/or adjusting at least one operational parameter of the system. The techniques provide increased accuracy over known statistical approaches to forecasting temperatures of storage objects, leading to increased performance gains in terms of IO latency, IO operations per second, and bandwidth.