Eduardo Balvis

Orange juice was investigated as a substrate for the production of novel kefir-like beverages using milk kefir grains (MKG) and water kefir grains (WKG). Fermentation was monitored for 48 h to characterize changes in physicochemical parameters, substrate consumption, metabolite production, microbial populations, antibacterial activity, vitamin and mineral composition, and volatile compounds. Both kefir grain types supported the growth of lactic acid bacteria, acetic acid bacteria, and yeasts, reaching final populations of approximately 6–7, 5–6, and 8 log CFU/mL, respectively. WKG promoted greater early production of lactic acid and consistently higher levels of acetic acid, ethanol, and antibacterial activity, whereas MKG produced a slightly higher lactic acid concentration after 48 h and was associated with greater increases in potassium, phosphorus, magnesium, and calcium. Vitamins B1, B2, and C decreased during fermentation with both MKG and WKG. The volatile profile was substantially altered during fermentation, with the potential aroma contribution shifting from predominantly balsamic and citrus notes toward fruity and sweet characteristics, particularly after 48 h. Overall, kefir grain type and fermentation time strongly influenced the physicochemical, microbiological, nutritional, antibacterial, and volatile characteristics of fermented orange juice. These findings demonstrate the potential of both grains for developing non-dairy kefir-like beverages.

This study evaluated the fermentation kinetics and properties of kefir beverages produced from whole milk using milk kefir grains (MKGs) or water kefir grains (WKGs) over 48 h. MKGs showed higher initial microbial loads and promoted rapid acidification, with pH decreasing from 6.70 to 4.99 and significant production of lactic acid (10.58 g/L) and ethanol (5.17 g/L), compared with WKGs (final pH 6.20, 6 CFU/mL—one of the requirements for conferring probiotic relevance to a beverage—with MKGs reaching higher counts. Lactose and protein consumption were greater in MKGs, suggesting more intense metabolic activity. Fermentation enhanced nutritional value by increasing vitamins B2, B3, B5, and pyridoxine, while vitamin D3 decreased. Mineral composition remained largely unchanged. Volatile analysis identified 31 compounds: MKGs favored fatty acids and lactones associated with creamy notes, whereas WKGs promoted ester formation and fruity aromas. Overall, both grain types produced microbiologically safe beverages with distinct biochemical and sensory profiles, demonstrating the feasibility of using WKGs for milk fermentation.

The coupled logistic models developed in this study, across various media (concen-trated whey (CW), diluted whey (DW), MRS, and TGE broths) and nutrient (glutamic acid or glucose) supplementation levels, revealed clear patterns in model performance for six culture variables. Biomass growth, lactic acid (LA) production, total antibacte-rial activity (TAA) synthesis, and pH evolution were generally well described by both uncoupled and coupled logistic models, with R² values above 0.9700. Coupling pro-vided moderate improvements for LA and TAA, particularly in glucose-supplemented DW media, by linking metabolite formation to biomass growth and pH decline, result-ing in more mechanistically and physiologically coherent models. The most pro-nounced benefits of coupling were observed for the consumption of total sugars (TS) and nitrogen (TN). In uncoupled models, R² values for TS and TN were often low or highly variable, whereas coupled models substantially increased R² (up to ~0.9990). These findings demonstrate that TS and TN consumption are strongly growth-associated processes and cannot be adequately modeled as independent phe-nomena. Overall, while uncoupled models are sufficient to describe growth, acidifica-tion, and metabolite formation, the coupled modeling approach provides a robust, in-tegrated framework that captures the interactions among biomass growth, nutrient utilization, and metabolite production.

Nowadays, consumer demand for functional foods with health benefits has grown significantly. In response to this trend, a variety of potentially probiotic foods have been developed—most notably kefir and kefir-like beverages, which are highly appreciated for their tangy flavor and health-promoting properties. Traditionally, kefir is made by fermenting cow’s milk with milk kefir grains, although milk from other animals—such as goats, ewes, buffalo, camels, and mares—is also used. Additionally, non-dairy versions are made by fermenting plant-based milks (such as coconut, almond, soy, rice, and oat) with the same type of grains, or by fermenting fruit and vegetable juices (e.g., apple, carrot, fennel, grape, tomato, prickly pear, onion, kiwifruit, strawberry, quince, pomegranate) with water kefir grains. Despite their popularity, many aspects of kefir production remain poorly understood. These include alternative production methods beyond traditional batch fermentation, kinetic studies of the process, and the influence of key cultivation variables—such as temperature, initial pH, and the type and concentration of nutrients—on biomass production and fermentation metabolites. A deeper understanding of the fermentation process can enable the production of kefir beverages tailored to meet diverse consumer preferences.

Railway infrastructures necessitate the inspection of various elements to ensure operational safety. This study concentrates on five key components: rail, sleepers and ballast, track geometry, and catenary. The operational principles of the primary defect measurement sensors are elaborated, emphasizing the use of ultrasound, eddy currents, active and passive optical elements, accelerometers, and ground penetrating radar. Each sensor type is evaluated in terms of its advantages and limitations. Examples of mobile inspection platforms are provided, ranging from laboratory trains to draisines and track trolleys. The authors foresee future trends in railway inspection, including the implementation of IoT sensors, autonomous robots, and geospatial intelligence technologies. It is anticipated that the integration of sensors within both infrastructure and rolling stock will enhance maintenance and safety, with an increased utilization of autonomous robotic systems for hazardous and hard-to-reach areas.

Thermal coating paints offer a passive strategy to reduce heat gain in buildings, improve ventilation, and lower energy consumption. This study investigates the effectiveness of these technologies by comparing different housing structures and environmental conditions. Specifically, it examines thermal envelope solutions for cool roofs in homes along the Colombian Caribbean Coast. We quantify the thermal impacts using experimental data collected from 120 houses across eight municipalities in the Magdalena Department, Colombia. The research details the technology and analytical methods employed, focusing on thermal reductions achieved through thermal coatings to potentially reduce energy demand. A comprehensive measurement system, incorporating temperature and humidity sensors, is developed to assess the impact of the coatings. Thermal comfort is evaluated according to the ASHRAE 55 standard, with temperature reductions calculated for each house treated with thermal coatings. A methodology is applied to evaluate the thermal reduction between a house with a coating solution versus a house without it. The results show a temperature reduction on a house-by-house basis, from 1.5% to 16%. On average, the results yield a significant 7% reduction in thermal load. Additionally, a mobile application is developed to disseminate the results of this research, promoting the social appropriation of science among the involved communities.

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced a significant surge in both civilian and military applications, owing to their versatility and cost-effectiveness. However, a negligent use or the operation with harmful intent of these aircraft poses a potential risk to public safety and the privacy of individuals. In response to this threat, counter-drone systems have been developed in recent years, including technologies to detect, position, and neutralize these aircraft. This paper presents a review of different existing commercial counter-drone systems, the technologies behind detection, tracking, and classification, as well as soft and hard kill mitigation.

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.

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.