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In recent years, CubeSat-type satellites have experienced tremendous growth, becoming one of the alternative paths for space technological development for multiple space agencies around the world. Within the design process of CubeSat satellites, the evaluation of the multiple subsystems is mandatory. Among the satellite’s vital subsystems is the Attitude Determination and Control System (ADCS), whose ground validation is crucial for the satellite’s mission. This subsystem is typically tested on ground using air-suspended test benches, which face a very specific problem related to the initial test conditions due to the low-friction environment that complicates the test’s execution. This article develops a Fuzzy-PID controller with a Mamdani-type inference system capable of resolving stability problems in one degree of freedom, based on a simplified model of traditional ADCS test benches.

Space exploration in recent years has seen growth, with Mars being the preferred destination for major space agencies. Among the multiple problems faced by robotic exploration systems (commonly called rovers) is the control of their orientation. For this, complex and highly non-linear dynamic models are used as a starting point. Among the models used is the lateral dynamics model, which takes into consideration factors such as sideslip, yaw rate, and lateral forces generated in the rover. This work presents a non-linear control law based on extended linearisation capable of orienting the rover to a certain angle according to an inertial reference frame.

Background In August 2017, Hurricane Harvey caused unprecedented flooding across the greater Houston area. Given the potential for widespread flood-related exposures, including mold and sewage, and the emotional and mental toll caused by the flooding, we sought to evaluate the short- and long-term impact of flood-related exposures on the health of Houstonians. Our objectives were to assess the association of flood-related exposures with allergic symptoms and stress among Houston-area residents at two time points: within approximately 30 days (T1) and 12 months (T2) after Hurricane Harvey’s landfall. Methods The Houston Hurricane Harvey Health (Houston-3H) Study enrolled a total of 347 unique participants from four sites across Harris County at two times: within approximately 1-month of Harvey (T1, n  = 206) and approximately 12-months after Harvey (T2, n  = 266), including 125 individuals who participated at both time points. Using a self-administered questionnaire, participants reported details on demographics, flood-related exposures, and health outcomes, including allergic symptoms and stress. Results The majority of participants reported hurricane-related flooding in their homes at T1 (79.1%) and T2 (87.2%) and experienced at least one allergic symptom after the hurricane (79.4% at T1 and 68.4% at T2). In general, flood-exposed individuals were at increased risk of upper respiratory tract allergic symptoms, reported at both the T1 and T2 time points, with exposures to dirty water and mold associated with increased risk of multiple allergic symptoms. The mean stress score of study participants at T1 was 8.0 ± 2.1 and at T2, 5.1 ± 3.2, on a 0–10 scale. Participants who experienced specific flood-related exposures reported higher stress scores when compared with their counterparts, especially 1 year after Harvey. Also, a supplementary paired-samples analysis showed that reports of wheezing, shortness of breath, and skin rash did not change between T1 and T2, though other conditions were less commonly reported at T2. Conclusion These initial Houston-3H findings demonstrate that flooding experiences that occurred as a consequence of Hurricane Harvey had lasting impacts on the health of Houstonians up to 1 year after the hurricane.

This paper describes the development of a deep neural network architecture based on transformer encoder blocks and Time2Vec layers for the prediction of electricity prices several steps ahead (8 h), from a probabilistic approach, to feed future decision-making tools in the context of the widespread use of intra-day DERs and new market perspectives. The proposed model was tested with hourly wholesale electricity price data from Colombia, and the results were compared with different state-of-the-art forecasting baseline-tuned models such as Holt–Winters, XGBoost, Stacked LSTM, and Attention-LSTM. The findings show that the proposed model outperforms these baselines by effectively incorporating nonlinearity and explicitly modeling the underlying data’s behavior, all of this under four operating scenarios and different performance metrics. This allows it to handle high-, medium-, and low-variability scenarios while maintaining the accuracy and reliability of its predictions. The proposed framework shows potential for significantly improving the accuracy of electricity price forecasts, which can have significant benefits for making informed decisions in the energy sector.

Shrimp fisheries are among the most important fisheries worldwide, and shrimp culture has increased considerably in recent years. Most current studies on reproduction-related genes have been conducted on cultured shrimp. However, gene expression is intimately linked to physiological and environmental conditions, and therefore an organism’s growth environment has a great influence on reproduction. Thus, gene expression profiling, should be applied in fisheries studies. Here, we identified the expression patterns of 76 reproduction-related genes in P. vannamei via the analysis of pooled transcriptomes from a time-series experiment encompassing a full circadian cycle. The expression patterns of genes associated both directly ( Vtg , ODP , and ProR ) and indirectly ( FAMet , CruA1 , and CruC1 ) with reproduction were evaluated, as these genes could be used as molecular markers of previtellogenic and vitellogenic maturation stages. The evaluated genes were prominently upregulated during vitellogenic stages, with specific expression patterns depending on the organism’s environment, diet, and season. Vtg , ProR , ODP , and FaMet could serve as molecular markers for both wild and cultured organisms.

Behavioral activation therapy is presented as a promising psychological intervention to enhance depression management and related symptoms by increasing engagement in rewarding activities. This study reviews three research endeavors, including randomized controlled trials and a case study. Variability in intervention duration and training approaches is noted, although typically, eight sessions per week were conducted. Therapy components range from participating in pleasurable activities to ongoing support outside sessions. The process of evidence source selection relied on identifying 327 articles across four databases, with three selected for review, utilizing the PRISMA extension for scoping reviews. This ensured rigorous eligibility criteria and a structured methodology for data collection. Overall, these findings support the effectiveness and applicability of behavioral activation therapy in treating depression in older adults. Training non-specialized healthcare personnel would improve the overall quality of medical care and facilitate the dissemination of evidence-based therapies. This, in turn, could be crucial in closing the psychotherapeutic care gap that exists in low and middle-income countries.

Fresh products demand natural preservatives without solvent traces. Calcium-based extraction of bioactive compounds from eggplant peels (EP), could be used as an alternative solvent-free natural antimicrobial food preservative agent. In this study, we extracted bioactive compounds from EP using different calcium salts (CaSO 4 , CaCO 3 , and CaCl 2 ) and evaluated the total phenolic and flavonoid contents, antioxidant activity, and bactericidal activity against Salmonella Typhimurium. The EP extracts obtained using 1% CaCO 3 exhibited the highest total phenolic content and pronounced antioxidant activity. All EP extracts decreased Salmonella concentration after 10 and 12 h. In infected-lettuce leaves, the 1% CaCO 3 EP extract inhibited bacterial growth at similar levels as a commercial disinfectant. The main compound identified in this EP extract was the chlorogenic acid. The extracts from EP obtained using calcium salts, represent a natural novel alternative preservative agent for the food industry, with antioxidant properties and potentially positive effects on human health.

Launching satellites into the Earth’s orbit is a critical area of research, and very demanding satellite services increase exponentially as modern society takes shape. At the same time, the costs of developing and launching satellite missions with shorter development times increase the requirements of novel approaches in the several engineering areas required to build, test, launch, and operate satellites in the Earth’s orbit, as well as in orbits around other celestial bodies. One area with the potential to save launching costs is that of the structural integrity of satellites, particularly in the launching phase where the largest vibrations due to the rocket motion and subsequent stresses could impact the survival ability of the satellite. To address this problem, two important areas of engineering join together to provide novel, complete, and competitive solutions: topology optimisation methods and additive manufacturing. On one side, topology optimisation methods are mathematical methods that allow iteratively optimising structures (usually by decreasing mass) while improving some structural properties depending on the application (load capacity, for instance), through the maximisation or minimisation of a uni- or multi-objective function and multiple types of algorithms. This area has been widely active in general for the last 30 years and has two main core types of algorithms: continuum methods that modify continuous parameters such as density, and discrete methods that work by adding and deleting material elements in a meshing context. On the other side, additive manufacturing techniques are more recent manufacturing processes aimed at revolutionising manufacturing and supply chains. The main exponents of additive manufacturing are Selective Laser Melting (SLM) (3D printing) as well as Electron Beam Melting (EBM). Recent trends show that topology-optimised structures built with novel materials through additive manufacturing processes may provide cheaper state-of-the-art structures that are fully optimised to better perform in the outer-space environment, particularly as part of the structure subsystem of novel satellite systems. This work aims to present an extended review of the main methods of structural topology optimisation as well as additive manufacture in the aerospace field, with a particular focus on satellite structures, which may set the arena for the development of future satellite structures in the next five to ten years.

Este libro surge en momentos donde la Inteligencia Artifical se ha convertido en una tecnología cada vez más presente en nuestras labores cotidianas, tiempos en los que aparecen serios cuestionamientos sobre sus beneficios. Incluso algunos estudiosos la consideran una tecnología que puede poner en riesgo a la humanidad y provocar un colapso de nuestra civilización. Como toda tecnología con este potencial, la IA tiene también un enorme margen para ser utilizada de manera positiva con posibilidades de lograr un impacto beneficioso para la sociedad. Lo anterior han generar una iniciativa denominada Inteligencia Artificial por el Bien Social.

Background The Zic family of transcription factors (TFs) promote both proliferation and maturation of cerebellar granule neurons (CGNs), raising the question of how a single, constitutively expressed TF family can support distinct developmental processes. Here we use an integrative experimental and bioinformatic approach to discover the regulatory relationship between Zic TF binding and changing programs of gene transcription during postnatal CGN differentiation. Results We first established a bioinformatic pipeline to integrate Zic ChIP-seq data from the developing mouse cerebellum with other genomic datasets from the same tissue. In newborn CGNs, Zic TF binding predominates at active enhancers that are co-bound by developmentally regulated TFs including Atoh1, whereas in mature CGNs, Zic TF binding consolidates toward promoters where it co-localizes with activity-regulated TFs. We then performed CUT&RUN-seq in differentiating CGNs to define both the time course of developmental shifts in Zic TF binding and their relationship to gene expression. Mapping Zic TF binding sites to genes using chromatin looping, we identified the set of Zic target genes that have altered expression in RNA-seq from Zic1 or Zic2 knockdown CGNs. Conclusions Our data show that Zic TFs are required for both induction and repression of distinct, developmentally regulated target genes through a mechanism that is largely independent of changes in Zic TF binding. We suggest that the differential collaboration of Zic TFs with other TF families underlies the shift in their biological functions across CGN development.