Hadamard, cosine, and noiselet bases are implemented into a digital holographic microscope based on single-pixel imaging with the capability to retrieve images of complex objects. The object is illuminated with coherent light modulated with different patterns deployed in a digital micromirror device, and the resulting fields are captured by single-pixel detection. For amplitude images, the experimental results of the three bases are evaluated with the peak SNR criteria. It is shown that the cosine basis recovers amplitude distributions with the best quality. Regarding phase images, the recovered ones compare well with those obtained with a CMOS camera.

Convolutional neural networks (CNNs) and digital holographic interferometry (DHI) can be combined to improve the calculation efficiency and to simplify the procedures of many DHI applications. In DHI, for the measurements of concentration differences between liquid samples, two or more holograms are compared to find the difference phases among them, and then to estimate the concentration values. However, liquid samples with high concentration difference values are difficult to calculate using common phase unwrapping methods as they have high spatial frequencies. In this research, a new method to skip the phase unwrapping process in DHI, based on CNNs, is proposed. For this, images acquired by Guerrero-Mendez et al. (Metrology and Measurement Systems 24, 19–26, 2017) were used to train the CNN, and a multiple linear regression algorithm was fitted to estimate the concentration values for liquid samples. In addition, new images were recorded to evaluate the performance of the proposed method. The proposed method reached an accuracy of 0.0731%, and a precision of ±0.0645. The data demonstrated a high repeatability of 0.9986, with an operational range from 0.25 gL⁻¹ to 1.5 gL⁻¹. The proposed method was performed with liquid samples in a cylindrical glass.

We present an alternative method to detect and measure the concentration changes in liquid solutions. The method uses Digital Holographic Interferometry (DHI) and is based on measuring refractive index variations. The first hologram is recorded when a wavefront from light comes across an ordinary cylindrical glass container filled with a liquid solution. The second hologram is recorded after slight changing the liquid’s concentration. Differences in phase obtained from the correlation of the first hologram with the second one provide information about the refractive index variation, which is directly related to the changes in physical properties related to the concentration. The method can be used − with high sensitivity, accuracy, and speed − either to detect adulterations or to measure a slight change of concentration in the order of 0.001 moles which is equivalent to a difference of 0.003 g of sodium chloride in solutions. The method also enables to measure and calculate the phase difference among each pixel of two samples. This makes it possible to generate a global measurement of the phase difference of the entire sensed region.

Urban agriculture in space-constrained cities requires compact, reproducible propagation systems. Therefore, the aim of this Technical Note is to design, implement, and functionally validate a low-cost, modular hydroponic chamber (SSHG) for early-stage vegetative propagation. This system couples DHT11-based temperature/RH monitoring with rule-based actuation—irrigation 4×/day and temperature-triggered ventilation—under the control of an Arduino Uno microcontroller; LED lighting was not controlled nor analyzed. Two 15-day trials with basil (Ocimum basilicum L.) yielded rooting rates of 61.7% (37/60) and 43.3% (26/60) under a deliberate minimal-input configuration without nutrient solutions or rooting hormones. Environmental summaries and spatial survival maps revealed edge-effect patterns and RH variability that inform irrigation layout improvements. The chamber, bill of materials, and protocol are documented to support replication and iteration. Thus, the SSHG provides a transferable baseline for educators and researchers to audit, reproduce, and improve small-footprint, controlled-environment propagation. Beyond its technical feasibility, the SSHG contributes to sustainability by leveraging low-cost, readily available components, enabling decentralized seedling production in space-constrained settings, and operating under a minimal-input configuration. In line with widely reported hydroponic efficiencies (e.g., lower water use relative to soil-based propagation), this open and replicable platform aligns with SDGs 2, 11, 12, and 13.

The present work investigates the quality and the chemical effects of dehydration, using a novel dehydration system based on an electromagnetic induction and low pressures technique, comparing it with the thermo-solar drying system. High oleic sunflower seeds, which are an important oil seed crop, were used due to the fact that they have a special place in the food industry. The seed samples were exposed to electromagnetic induction and low pressures by 0.5 and 1 h, then several chemical characterizations were carried out, in the electrophoresis study, it was found that most proteins in the hull were degraded or denatured, some of them were lost during the time in the thermosolar dryer while in kernel keeps 94.9% of the concentration in control proteins. Otherwise, the electromagnetic induction dryer did not lose the most of proteins in the kernel keeping 99.1% in 0.5 h and 98.4% in 1 h, just degrading its concentration. Germination viability results did not show changes after 0.5 h in the electromagnetic fields, but they decreased in 1 h from 66 to 40% until the thermosolar method fell to 24% in 4 h, both analysis results change proportionally with the treatment time and moisture content and the amount of the oxygen.

This study reports the thermodynamic performance of a patented compact vertical evaporator–absorber unit for LiBr–H₂O absorption cooling, extending Part I by translating validated prototype data into a rigorous control-volume assessment of coupled transport. Coolant-side calorimetry was used to determine the absorption heat-transfer rate (Q_abs), while a mass–energy balance provided an estimate of the absorption mass-transfer rate (${∆\dot{m}}_{abs}$) across twelve manually imposed thermal-load phases with tagged fan-OFF/ON sub-intervals. Linear trend (slope) analysis was applied to quantify phase-resolved dynamic behavior. Fan assistance produced three load-dependent regimes: (i) stabilization of downward trends under low and zero loads, yielding slope-based relative improvements above 100% in the most critical weak-gradient phases; (ii) acceleration of recovery at intermediate loads; and (iii) moderation of strongly positive drifts at high loads. The global thermal resistance ($R_{th}$) decreased by more than 30% in passive and low-load phases, and Wilcoxon signed-rank tests confirmed statistically significant reductions in most intervals (p < 0.05). Uncertainty contributions and robustness were quantified through an uncertainty budget decomposition and sensitivity analyses, and a subsystem-level normalization (η_EA = Q_abs/Q_in) is reported to support comparisons across loads without invoking cycle COP. Overall, active vapor-flow management using a low-power internal fan widens the useful operating envelope of compact absorbers and provides a validated thermodynamic baseline with practical, regime-aware control guidelines for decentralized low-carbon cooling technologies.