In the pursuit of energy efficiency and reduced environmental impact, adequate ventilation in enclosed spaces is essential. This study presents a hybrid neural network model designed for monitoring and prediction of environmental variables. The system comprises two phases: An IoT hardware–software platform for data acquisition and decision-making and a hybrid model combining short-term memory and convolutional recurrent structures. The results are promising and hold potential for integration into parallel processing AI architectures.

We analyze quantum droplets formed in a two-dimensional symmetric mixture of Bose-Einstein condensed atoms. For sufficiently large atom numbers, these droplets exhibit a flattop density profile with sharp boundaries governed by surface tension. Within the bulk of the droplet, traveling matter waves-localized density dips-can propagate at constant velocity while maintaining their shape. Using numerical simulations and qualitative analysis, we investigate the rich phenomenology that arises when such excitations reach the boundary of a finite droplet. We show that they can emit a small outgoing droplet, excite internal modes of the host soliton, or, in the case of vortex-antivortex pairs, split into individual vortices propagating backward near the edge. Furthermore, we demonstrate that traveling waves can be dynamically generated near the boundary through the collision of distinct droplets, and we discuss their trajectories and interactions.

The generation of mathematical models for the analysis of buildings with multiple thermal zones is a large and complex task. Furthermore, the order and complexity of the dynamical model are increased by the number of included thermal zones. To overcome this problem, this paper presents an algorithm to define the mathematical model automatically, using the geometric and physics parameters as inputs. Additionally, the spatial position of each thermal zone must be recorded in an arrangement called a contact matrix. The algorithm for modeling systems with multiple thermal zones is the main contribution of this work. This algorithm is presented in pseudocode format and as an annex, an implementation in MATLAB software. One of the advantages of this methodology is that it allows us to work with parallelepipeds and not necessarily cubic thermal zones. The algorithm allows us to generate mathematical models with symbolic variables, starting from the knowledge of how many thermal zones compose the system and its geometric organization. This information must be organized in a matrix arrangement called a contact matrix. Different arrays of thermal zones were constructed with wooden boxes to verify the functionality of the models generated with the algorithm. Each case provided information that allowed us to adjust the mathematical models and their simulations, obtaining a range of errors between experimental and simulated temperatures from $2.08$ to $5.6$, depending on the number of thermal zones studied.

Typical laboratory experiments in the introductory undergraduate physics course, such as those studying the series RC,1–3 RL,4 and RLC5–9 circuits, use signal g Typical laboratory experiments in the introductory undergraduate physics course, such as those studying the series RC,1–3 RL,4 and RLC5–9 circuits, use signal g

In the pursuit of energy efficiency and reduced environmental impact, adequate ventilation in enclosed spaces is essential. This study presents a hybrid neural network model designed for real-time monitoring and prediction of environmental variables. The system comprises two phases: An IoT hardware-software platform for data acquisition and decision-making, and a hybrid model combining short-term memory and convolutional recurrent structures. The results are promising and hold potential for integration into parallel processing AI architectures.

This study presents experimental results on capacitance fluctuations in several devices located within an interleaving structure. Specifically, it examines the behavior of the capacitance between the anode and cathode of a photomultiplier, comparing it with the characteristics of the ultra-stable capacitor analyzed in via measurements inside and outside a modified Faraday cage. The results cover spectral and correlation analyses both inside and outside the box, confirming differences in the spectrum using the periodograms. In particular, the confidence intervals for the mean capacitance values show significant changes between the two scenarios, from the inside to the outside of the enclosure. In the case of the ultra-stable capacitor, there is an increase from 0.004 to 0.008 nF. On the other hand, a symmetry analysis is conducted for all measurements taken both outside and inside the modified Faraday cage. It is observed that in all cases, there is clear non-symmetric behavior in the data.