The present disclosure provides a microfluidic device and system for measuring a composite electropharyngeogram (EPG) signal from a pool of multiple nematodes, wherein the composite EPG signal is measured from the pool of nematodes present in a single recording channel connected to two or more integrated electrodes. The microfluidic device includes an inlet port and outlet port directly connected to a single recording channel and two or more electrodes directly connected to the recording channel. The recording channel is configured to hold 10 to 10,000 nematodes.

The present disclosure provides a microfluidic device and system for measuring a composite electropharyngeogram (EPG) signal from a pool of multiple nematodes, wherein the composite EPG signal is measured from the pool of nematodes present in a single recording channel connected to two or more integrated electrodes. The microfluidic device includes an inlet port and outlet port directly connected to a single recording channel and two or more electrodes directly connected to the recording channel. The recording channel is configured to hold 10 to 10,000 nematodes.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for estimating wave properties of a body of water. A computer-implemented system obtains measurement data for a duration of time from an inertial measurement unit (IMU) onboard an underwater device, generates model input data based on at least the measurement data obtained at the plurality of time points, and processes the model input data to generate model output data indicating one or more wave properties using a machine-learning model. The system further determines, based on at least the one or more wave properties, whether the device is safe to be deployed.

One variation of a method includes: accessing a video feed recorded at a training apparatus configured to dispense primary reinforcer units; dispensing a first primary reinforcer unit toward a first location; in response to detecting the animal at the first location, dispensing a second primary reinforcer unit toward a second location intersecting a pathway extending from the first location; in response to detecting movement of the animal along the pathway, collecting a timeseries of position data representing changes in position of a set of anatomical features of the animal; based on the timeseries of position data, deriving a movement profile representing movement of the animal along the pathway; based on a difference between the movement profile and a baseline movement profile defined for the animal, interpreting an abnormality and predicting a causal pathway for the abnormality; and selecting a mitigation protocol based on the causal pathway.

Injectable biophotonic sensors, systems relating to biophotonic sensors, and methods of using the injectable biophotonic sensors and systems are described. Methods and devices for delivering injectable biophotonic sensors to a subject are described. In an embodiment, an injectable biophotonic sensor comprises a printed circuit board (PCB); a light source; a first sensing element; a second sensing element; a receiver device or a induction coil; and an outer casing, wherein the first sensing element, the second sensing element, and the receiver device or the receiver induction coil are coupled to the PCB.

Systems, methods, and apparatuses for performing analytics for equine-related conditions from fetlock sensors include receiving sensor data from one or more sensors attached to one or more fetlock wearable devices. Each of the one or more fetlock wearable devices are configured to attach to a fetlock of a respective limb of a horse. The analytics system compares the sensor data to one or more baseline measurement values. The analytics system detects a condition responsive to comparing the sensor data to one or more baseline measurement values. The analytics system transmits an alert to one or more remote devices responsive to detecting the condition.

An animal tag includes a first electronic tag for implanting in an animal, the first electronic tag is provided with a first identification feature, and the first identification feature is configured for binding to the animal information of the animal. The mobile interaction device includes: an information transmission module, which carries instruction information and is provide outside the animal to transmit the instruction information to the mobile network terminal, so that the mobile network terminal can connect with a server to query the animal information; wherein, the instruction information includes retrieval information and domain name information of the server; and the retrieval information uniquely corresponds to the first identification feature, or uniquely corresponds to the animal information bound to the first identification feature. The disclosure relates to an animal tag system, a method for modifying the animal tag and a method for querying the information of the animal tag.

An apparatus for detecting mounting behavior of an animal object includes: a memory that stores a program; and a processor that executes the program. The program extracts animal detection information about an animal object detected from the image by inputting the received image into an animal detection model. Also, the program extracts bounding boxes of which a distance between coordinates of central points is smaller than a first set value, bounding boxes of which a difference in rotational angle is smaller than a second set value, and bounding boxes of which a difference between a vector connecting the central points of the extracted bounding boxes and an orientation of each bounding box is smaller than a third set value. If activity information of the animal object is extracted based on an MHI of the image, it is determined that mounting behavior occurs.

A method, device, and system for determining a body attribute of an animal may be provided. For example, a system may include a sensor configured to capture image data relating to the animal. One or more processors may be configured to receive the captured image data relating to the animal; identify portions relating to the animal depicted within the image data; input, into a machine learning model, the portions relating to the animal depicted within the image data; and determine, via the machine learning model, an ideal body weight (IBW), a body condition score (BCS) of the animal, a body fat index (BFI) of the animal, a weight or other attributes of the animal or part of the animal including height, width, length, depth, diameter, radius, circumference, and the like.

Embodiments described herein provide systems for stimulating a desired response, such as ovulation and egg laying, hunger, growth, mood and sexual maturity in birds, such as chickens, turkeys, ducks, quail and ostrich, by controlling the duty cycle, wavelength band and frequency of photon bursts to a bird, through the high frequency modulation of photons in an individual color spectrum to the bird and duty cycle, where the photon modulation and duty cycle is based upon the specific needs of the bird.