Sensors Data Analysis in Supervisory Control and Data Acquisition (SCADA) Systems to Foresee Failures with an Undetermined Origin.

This paper presents the design and implementation of a supervisory control and data acquisition (SCADA) system for automatic fault detection. The proposed system offers advantages in three areas: the prognostic capacity for preventive and predictive maintenance, improvement in the quality of the machined product and a reduction in breakdown times. The complementary technologies, the Industrial Internet of Things (IIoT) and various machine learning (ML) techniques, are employed with SCADA systems to obtain the objectives.

DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data.

Single-cell RNA sequencing (scRNA-seq) data provides unprecedented information on cell fate decisions; however, the spatial arrangement of cells is often lost. Several recent computational methods have been developed to impute spatial information onto a scRNA-seq dataset through analyzing known spatial expression patterns of a small subset of genes known as a reference atlas. However, there is a lack of comprehensive analysis of the accuracy, precision, and robustness of the mappings, along with the generalizability of these methods, which are often designed for specific systems.

Effective generalized predictive control of induction motor.

In this document it is presented and experimentally validated a new linear predictive regulator to control the mechanical speed and the rotor flux of induction motor (IM). The regulator is developed in the synchronous reference frame and it provides a very good dynamic performance and guarantees fulfilment with the current constraints, to avoid over currents in stator windings. This predictive controller employs the minimum necessary dynamic model of the motor to get minor computational cost, in which the rotor flux and the load torque are estimated, and in spite of important parametric uncertainties, the performance is excellent.

Ovulation induction in rabbit does submitted to artificial insemination by adding buserelin to the seminal dose.

This study was aimed at determining if a GnRH analogue, buserelin, could be used for ovulation induction in rabbit does submitted to artificial insemination (AI) by intravaginal administration, by adding the hormone to the seminal dose. In a first experiment, 39 secondiparous experimental does (Hyplus strain PS19, Grimaud Frères, France, of about 30 weeks of age) were divided into 3 groups of 13 does each, which at the moment of AI received the following treatments, respectively: (1) control: an intramuscular injection of buserelin (0.8 microg/doe), (2) 8 microg/doe of buserelin added to the insemination dose, and (3) 16 microg/doe of buserelin added to the insemination dose.

Reproductive performance of multiparous rabbit lactating does: effect of lighting programs and PMSG use.

This study aims to determine if Pregnant Mare Serum Gonadotrophin (PMSG), used for oestrous synchronization in multiparous lactating does, could be replaced by one of the following lighting schedules without impairing reproductive performance: (a) 12-h L (light)/12-h D (dark) or (b) 8-h L/16-h D, until day 6 before artificial insemination (AI), when in both cases photoperiod was changed to 16-h L/8-h D and maintained until the day of AI, and in the following 4 days post Al the light hours were progressively reduced to the initial schedules. Two groups of 20 does each were respectively submitted to one of the lighting schedules specified above. All does were artificially inseminated in 6 consecutive cycles at 42 days intervals.