The design and implementation of a fuzzy logic controller (FLC) are presented, offering a solution to improve the irrigation of rose crops. The objective is to reduce the water consumption and operative costs, taking advantage of intelligent controllers and environmental characteristics in a specific region. Considering that the main controllable variables that affect the growth of plants are relative humidity (RH) and temperature (T), in this study, these variables are used to create a system whose aim is to provide an adequate amount of water for a rose crop in the State of Mexico. The Mamdani method was used for the FLC design and the membership functions, while the area centroid was considered as the defuzzification strategy. After implementing the FLC proposal using a field-programmable gate array (FPGA) in a domestic greenhouse, integrated by an array of [5 × 3] rose plants under natural restrictions, a reduction of 0.2 L per week with respect to the traditional manual irrigation system was found. The proposed design highlights the technological advantages of using a fuzzy logic-controlled irrigation system over traditional methods.

In this paper, we propose a model of a parameter estimator filter for Black Box-type Stochastic Systems (BBSS), that is, only its inputs and outputs are known; considering its intrinsic properties observed in the second probability moment, in which the probability has the description of a specific distribution function relative to the random variables and the law of large numbers, allowing the stochastic system to be described with a Gaussian Distribution Function (GDF) and its linear transformation core in the Taylor series. Commonly, all estimates are assumed in the Second Moment of Probability (SMP) with equiprobable conditions, but in this case, a specific description of the Probability Distribution Function (PDF) is considered a priori, which is a contribution to the theory of digital filtering in estimation for signal reconstruction. The simulation of the parameter estimation is carried out for a given reference signal, maintaining the stability of the system in discrete time, and a comparison is made between the estimator based on the SMP and the PDF to observe the level of convergence, where the PDF approach has a better performance respect to the SMP one.

Nonstationary stochastic systems in the Wiener-Kolmogorov sense have properties defined by their moments of probability, entropy, and distribution function. Filtering Theory, in general, describes indirectly, a stochastic system through the processes of parameter estimation and state identification. The objective of this article is to develop a Recursive Filter with an Exponential Kernel (RFEK) to reconstruct the response of a nonstationary stochastic system. To achieve this, first, a system viewed as a Black Box (BB) is analyzed. These systems are that which its internal dynamics is unknown, only input-output is known and from which a set of responses is measured with respect to a particular excitation. From these measurements and applying the proposed filter, a set of estimated parameters and identified states are obtained as a characterization of the system. Subsequently, a comparison is made between the filter output signal and the reference signal over time; that is, measuring their point-to-point convergence. The convergence of the stochastic reference makes it possible to indirectly observe its stability from a bounded estimation region. As a case study, bioelectric signals of the electroencephalographic (EEG) type are analyzed giving an improved approximation with respect to the Kalman filter results.

The ATP-binding cassette transporter A1 (ABCA1) functional variant R230C (rs9282541) is associated with low plasma HDL-C levels, yet its atomic-scale mechanism remains unclear. We evaluated the structural and dynamic impact of R230C compared to wild-type (WT) ABCA1 using 200 ns molecular dynamics simulations in a lipid raft membrane. While the tertiary fold was preserved, R230C exhibited reduced overall flexibility (lower RMSD and localized RMSF rigidification) alongside a slightly expanded conformation (increased Rg and SASA). Localized fluctuations near residue 230 in extracellular domain 1 (ECD1) were coupled with decreased dynamic heterogeneity in distal functional regions, particularly nucleotide-binding domain 2 (NBD2) and transmembrane domain 2 (TMD2). MOSAICS analysis revealed subtle alterations in membrane thickness, midplane displacement, and lipid orientation. Furthermore, CAVER tunnel analysis demonstrated increased pathway heterogeneity (17 clusters in R230C vs. 10 in WT), lower persistence, and smaller bottleneck radii, disrupting the primary cholesterol transport route. Thus, R230C acts as a dynamic allosteric modulator and membrane-coupling agent rather than a folding-disruptive mutation, providing a biophysical rationale for reduced cholesterol efflux and low plasma HDL-C levels.