A heating, ventilation, or air conditioning (HVAC) system for one or more building zones includes airside HVAC equipment operable to provide clean air to the one or more building zones and a controller. The controller is configured to obtain a dynamic temperature model and a dynamic infectious quanta model for the one or more building zones, determine an infection probability, and generate control decisions for the airside HVAC equipment using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability.

A method for managing air quality may include, at one or more processors, receiving sensor data comprising a plurality of air quality parameters for an environment, wherein the sensor data is generated by one or more environment quality monitoring devices located in the environment, predicting an adverse air quality event based on the sensor data, and automatically controlling one or more devices to mitigate the adverse air quality event. An environment quality monitoring device may include a housing, a plurality of sensors in the housing and configured to generate sensor data comprising a plurality of environment quality parameters, a network communication device configured to communicate the sensor data over a network, and an alert configured to indicate an environment quality score of the ambient environment, where the environment quality score is based on at least a portion of the sensor data.

A self-configuring controller includes one or more processors and one or more non-transitory machine readable media storing instructions. When executed by the one or more processors, the instructions cause the one or more processors to receive an output signal from a controlled system or device representative of an operation of the controlled system or device in response to a first perturbed control input perturbed using a first dither signal, estimate a bandwidth of the controlled system or device based on the output signal and the first dither signal, perturb a second control input using a second dither signal based on the bandwidth of the controlled system or device to generate a second perturbed control input, and transmit the second perturbed control input to the controlled system or device.

A method of determining multimodal polyethylene quality comprising the steps of (a) providing a multimodal polyethylene resin sample; (b) determining, in any sequence, the following: that the multimodal polyethylene resin sample has a melt index within 30% of a target melt index; that the multimodal polyethylene resin sample has a density within 2.5% of a target density; that the multimodal polyethylene resin sample has a dynamic viscosity deviation (% MVD) from a target dynamic viscosity of less than about 100%; that the multimodal polyethylene resin sample has a weight average molecular weight (M.sub.w) deviation (% M.sub.wD) from a target M.sub.w of less than about 20%; and that the multimodal polyethylene resin sample has a gel permeation chromatography (GPC) curve profile deviation (% GPCD) from a target GPC curve profile of less than about 15%; and (c) responsive to step (b), designating the multimodal polyethylene resin sample as a high quality resin.

A system and approach for verifying and validating a room condition and its behavior in a critical environment. The system and approach may be a room controller built on top of a Niagara™ framework or launched from a Niagara workbench, and leverages extensible of Niagara. The system and approach may be web-based and used to test and verify the room condition per preset conditions. The system may have steps or tabs. They may incorporate screens for a create/open task, select test zone, read flow, hood/booster, T-stat set-up or temperature lever set-up, visual checks, and a report. One may create a new task and edit any existing task on the controller. One may move from task to task in either direction or go directly to the report of a completed task.

A method of determining multimodal polyethylene quality comprising the steps of (a) providing a multimodal polyethylene resin sample; (b) determining, in any sequence, the following: that the multimodal polyethylene resin sample has a melt index within 30% of a target melt index; that the multimodal polyethylene resin sample has a density within 2.5% of a target density; that the multimodal polyethylene resin sample has a dynamic viscosity deviation (% MVD) from a target dynamic viscosity of less than about 100%; that the multimodal polyethylene resin sample has a weight average molecular weight (M.sub.w) deviation (% M.sub.wD) from a target M.sub.w of less than about 20%; and that the multimodal polyethylene resin sample has a gel permeation chromatography (GPC) curve profile deviation (% GPCD) from a target GPC curve profile of less than about 15%; and (c) responsive to step (b), designating the multimodal polyethylene resin sample as a high quality resin.

Examples disclosed herein relate to an energy device including a memory, one or more processors, a transceiver, a display, and a dashboard. The memory includes one or more energy modules. The one or more processors are configured to communicate via the transceiver with one or more energy devices. The display is configured to display a dashboard of energy options based on one or more signals received from the one or more processors.

Method and environment controller using a neural network for bypassing a legacy environment control software module. The environment controller receives at least one environmental characteristic value and determines a plurality of input variables. At least one of the plurality of input variables is based on one among the at least one environmental characteristic value. The environment controller transmits the plurality of input variables to an inference server executing a neural network inference engine. The environment controller receives at least one inferred output variable from the inference server. The environment controller uses the at least one inferred output variable received from the inference server in place of at least one output variable calculated by the legacy environment control software module based on the plurality of input variables. The environment controller may prevent the execution of the legacy software module or overwrite the output variable(s) calculated by the legacy software module.

A method, device and system to facilitate centralized control and monitoring of remote network-enabled bathing unit systems owned and operated by different customers are described. A Graphical User Interface (GUI) is provided for presenting on a computing device a listing of bathing unit systems owned and operated by different customers. The GUI is also configured for displaying operational status indicators associated with at least some of the bathing unit systems presented in the listing of bathing unit systems. Data conveying updated operational status information pertaining to one or more of the bathing unit systems in the listing of bathing unit systems is received over a communication network and, in response, the GUI is dynamically adapted to display updated operational status indicators. User operable inputs may also be provided by the GUI to allow a user to add a new entry to the listing of bathing unit systems. In some implementations, the GUI may be configured to present information conveying one or more replacement parts available for purchase for the bathing unit systems in the displayed listing.

An integrated system for determining a hemostasis and oxygen transport parameter of a blood sample, such as blood, is disclosed. The system includes a measurement system, such as an ultrasonic sensor, configured to determine data characterizing the blood sample. For example, the data could be displacement of the blood sample in response to ultrasonic pulses. An integrated aspect of the system may be a common sensor, sample portion or data for fast and efficient determination of both parameters. The parameters can also be used to correct or improve measured parameters. For example, physiological adjustments may be applied to the hemostatic parameters using a HCT measurement. Also, physical adjustments may be applied, such as through calibration using a speed or attenuation of the sound pulse through or by the blood sample. These parameters may be displayed on a GUI to guide treatment.