In this article, various investigations on soft exoskeletons are presented and their functional and structural characteristics are analyzed. The present work is oriented to the studies of the last decade and covers the upper and lower joints, specifically the shoulder, elbow, wrist, hand, hip, knee, and ankle. Its functionality, applicability, and main characteristics are exposed, such as degrees of freedom, force, actuators, power transmission methods, control systems, and sensors. The purpose of this work is to show the current trend in the development of soft exoskeletons, in addition to specifying the essential characteristics that must be considered in its design and the challenges that its construction implies.

One of the separation processes used for the production and purification of hydrogen is molecular sieve adsorption using the Pressure Swing Adsorption (PSA) method. The process uses two beds containing activated carbon and a sequence of four steps (adsorption, depressurization, purge, and repressurization) for hydrogen production and purification. The initial composition is 0.11 CO, 0.61 H₂, and 0.28 CH₄ in molar fractions. The aim of this work is to bring the purity of hydrogen to 0.99 in molar fraction and implement controllers that can maintain the desired purity even in the presence of the disturbances that occur in the PSA process. The controller design (discrete PID and state feedback control) was based on the Hammerstein–Wiener model, which had an 80% fit over the rigorous PSA model. Both controllers were validated on a virtual plant of the PSA process, showing great performance and robustness against disturbances. The results obtained show that it is possible to follow the desired trajectory and attenuate double disturbances, while managing to maintain the purity of hydrogen at a value of 0.99 in molar fraction, which meets the international standards to be used as a biofuel.

Today, there are new technologies to produce bioethanol: one of them is the Pressure Swing Adsorption (PSA) process. This process has displaced other separation technologies due to the use of natural adsorbents and its methodology to obtain high purities with a lower energy cost. The aim of this work focuses on the optimization of the PSA process (experimental case) to obtain a higher recovery and production of bioethanol using lower energy consumption. The results are favorable since the energy cost is reduced to a range of 60% and 62%, obtaining purities above 99% wt of ethanol and recovery between 75% and 77.41%. The bioethanol produced and purified in the different scenarios meets international standards to be used as a fuel or oxygenating additive.

Adsorption processes are characterized by their kinetics and equilibrium isotherms described by mathematical models. Nowadays, adsorption with molecular sieves is a method used to separate certain elements or molecules from a mixture and produce hydrogen, nitrogen, oxygen, ethanol, or water treatment. This study had two main objectives. The first one was focused on the use of different natural (Clinoptilolite-S.L. Potosi, Clinoptilolite-Puebla, and Heulandite-Sonora) and synthetic (Zeolite Type 3A) adsorbents to separate the mixtures $H_{2}O/H_{2}S{O}_4$ and $H_{2}O/C_2{H}_{5}OH$ . It was determined that both Zeolite Type-3A and Heulandite-Sonora have greater adsorption capacity in a shorter time compared with the Clinoptilolites at different temperatures. The second objective was the simulation of a pressure swing adsorption process to dehydrate ethanol using the parameters obtained from Zeolite Type 3A (with maximum adsorption capacity). Several configurations were considered to calculate the appropriate nominal values for the optimal process. The results illustrate that the purity of ethanol is increased when the following parameters are considered in the adsorption process: a high pressure, a constant temperature between 100 and 120 ${}^{°}$ C, a feed composition near the azeotropic point with lower water content, and a purge pressure near the vacuum. Finally, the results show that it is possible to take advantage of the length of the absorber bed in order to reduce the energy costs by increasing the ethanol production as well as complying with the international purity standards.

The evoked potential is a neuronal activity that originates when a stimulus is presented. To achieve its detection, various techniques of brain signal processing can be used. One of the most studied evoked potentials is the P300 brain wave, which usually appears between 300 and 500 ms after the stimulus. Currently, the detection of P300 evoked potentials is of great importance due to its unique properties that allow the development of applications such as spellers, lie detectors, and diagnosis of psychiatric disorders. The present study was developed to demonstrate the usefulness of the Stockwell transform in the process of identifying P300 evoked potentials using a low-cost electroencephalography (EEG) device with only two brain sensors. The acquisition of signals was carried out using the Emotiv EPOC^® device—a wireless EEG headset. In the feature extraction, the Stockwell transform was used to obtain time-frequency information. The algorithms of linear discriminant analysis and a support vector machine were used in the classification process. The experiments were carried out with 10 participants; men with an average age of 25.3 years in good health. In general, a good performance (75–92%) was obtained in identifying P300 evoked potentials.