Abstract: A method including training, by one or more processors, a generative AI model using a plurality of first service requests handled by technicians for servicing building equipment. The generative AI model may be trained to predict root causes of a plurality of first problems corresponding to the plurality of first service requests. The method may include receiving, by the one or more processors, a second service request for servicing building equipment. The method may include predicting, by the one or more processors using the generative AI model, a root cause of a second problem corresponding to the second service request based on characteristics of the second service request and one or more patterns or trends identified from the plurality of first service requests using the generative AI model.

Abstract: A method including training, by one or more processors, a generative AI model using a plurality of first unstructured service reports corresponding to a plurality of first service requests handled by technicians for servicing building equipment. The plurality of first unstructured service reports include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method includes receiving, by the processors, a second service request for servicing building equipment. The method includes generating, by the processors using the generative AI model, a user interface prompting a user to provide information about a problem leading to the second service request as unstructured data not conforming to the predetermined format or conforming to the plurality of different predetermined formats.

Abstract: A method includes receiving, by one or more processors, an unstructured service report corresponding to a service request handled by one or more technicians for servicing building equipment. The unstructured service report may include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method may include extracting, by the one or more processors, a set of standards from one or more technical documents associated with the building equipment. The method may include automatically generating, by the one or more processors using a generative AI model, a structured service report in the predetermined format for delivery to a customer associated with the building equipment. Generating the structured service report may include standardizing the structured service report to comply with the set of standards extracted from the one or more technical documents associated with the building equipment.

Abstract: A method including training, by one or more processors, a generative AI model using first operating data from building equipment and a plurality of first service reports indicating a plurality of first problems associated with the building equipment. The method may include predicting, by the one or more processors using the generative AI model, one or more future problems likely to occur with the building equipment based on second operating data from the building equipment. The method may include automatically initiating, by the one or more processors, one or more actions to prevent the one or more future problems from occurring or mitigate an effect of the one or more future problems.

Abstract: A method includes receiving, by one or more processors, a plurality of first unstructured service reports corresponding to a plurality of first service requests handled by technicians for servicing building equipment. The plurality of first unstructured service reports may include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method may include training, by the one or more processors, a generative AI model using the plurality of first unstructured service reports. The method may include performing, by the one or more processors using the trained generative AI model, one or more actions with respect a second service request subsequent to training the generative AI model.

Abstract: A method includes receiving, by one or more processors, unstructured service data corresponding to one or more service requests handled by technicians for servicing building equipment of a building. The method may include detecting, by the one or more processors, an identifier of the building equipment, a space of the building, or a customer associated with the building using the unstructured service data. The method may include retrieving, by the one or more processors based on the identifier of the building equipment, the space, or the customer, additional data associated with the building equipment, the space, or the customer from one or more additional data sources separate from the unstructured service data. The method may include training, by the one or more processors, a generative AI model using training data including the unstructured service data and the additional data.

Abstract: A method includes training, by one or more processors, a generative AI model using a plurality of first service requests handled by technicians for servicing building equipment and outcome data indicating outcomes of the plurality of first service requests. The generative AI model may be trained to identify one or more patterns or trends between characteristics of the plurality of first service requests and the outcomes of the plurality of first service requests. The method may include receiving a second service request for servicing building equipment. The method may include automatically determining, using the generative AI model, one or more responses to the second service request based on characteristics of the second service request and the one or more patterns or trends between the characteristics of the plurality of first service requests and the outcomes of the plurality of first service requests identified using the generative AI model.

Abstract: A method includes training, by one or more processors, a generative AI model using training data including a plurality of first service requests indicating a plurality of first problems associated with building equipment and a plurality of first actions performed in response to the plurality of first service requests. The method may include receiving, by the one or more processors, a second service request indicating a second problem associated with building equipment. The method may include automatically determining, by the one or more processors using the generative AI model, one or more second actions to perform based on characteristics of the second service request. The method may include automatically initiating, by the one or more processors, the one or more second actions to address the second problem associated with the building equipment.

Abstract: A set of data elements is received. For each feature of a set of features, a corresponding reference distribution for the set of data elements is determined. For each feature of the set of features, one or more corresponding subset distributions for one or more subsets sampled from the set of data elements are determined. For each feature of the set of features, the corresponding reference distribution is compared with each of the one or more corresponding subset distributions to determine a corresponding distribution of divergences. At least the determined distributions of divergences for the set of features are provided for use in automated data analysis.

Abstract: A method includes receiving, by one or more processors, an unstructured service report corresponding to a service request handled by one or more technicians for servicing building equipment. The unstructured service report may include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method may include automatically generating, by the one or more processors using a generative AI model, a structured service report in the predetermined format for delivery to a customer associated with the building equipment. The structured service report may include additional content generated by the generative AI model and not provided within the unstructured service report.

Abstract: The invention relates to a single-use protective cover (1) intended to house a sphygmomanometer cuff and to adapt to the shape thereof, comprising a lower portion provided with an open side allowing the sphygmomanometer cuff to be inserted, wherein said protective sleeve (1) is made from a single piece of a hydrophobic material of SMS type consisting of a non-woven fabric comprising a top layer of spunbond polypropylene, a middle layer of blow-moulded polypropylene and a bottom layer of spunbond polypropylene, said protective sleeve (1) thus acting as a barrier against the risk of infection.

Abstract: An aircraft wing with a root, a tip, an inboard wing part, an outboard wing part, and a junction between the inboard wing part and the outboard wing part. The inboard wing part has anhedral and is swept back so that it extends downwardly and aft away from the root towards the junction. The outboard wing part has dihedral and is swept forward so that it extends upwardly and forward away from the junction towards the tip. An engine and landing gear are mounted at the junction. An aircraft with a pair of such wings has a W-shaped profile viewed from above, and an inverted gull-wing profile viewed from the front.

Abstract: A method for converting methane by an oxidative coupling reaction to longer chain hydrocarbons comprising cofeeding methane and oxygen simultaneously and continuously into a reaction zone to form a mixture, contacting said methane and oxygen mixture under oxidative coupling reaction conditions with a solid catalyst consisting essentially of manganese oxide and silicon oxide, promoted with an alkaline metal and non metal, to form longer chain hydrocarbons wherein the manganese, silicon oxide, alkali metal and non metal are present in a molar ratio 0-0.5:93.2-93.7:4.2:2.1.

Abstract: An improved method for the oxidative conversion of methane into higher hydrocarbons in which methane and oxygen are continuously and simultaneously cofed into a reaction zone under effective oxidative coupling conditions and contacted with a solid catalyst consisting essentially of a catalyst having a composition of empirical formula Ce.sub.a Na.sub.b Ca.sub.100 O.sub.x wherein a is in the range 0.03 to 2.0, b is in the range of 0.7 to 7.0 and oxygen is present in a molar amount sufficient to fulfill the valence requirements of cerium, sodium and calcium.