Vegetation identification using remote sensing is essential for understanding terrestrial ecosystems and monitoring climate change. This technology by providing high-resolution images of the Earth's surface from satellites, aircraft, and drones has revolutionized the way scientists study and un-derstand vegetation patterns, providing information on the distribution, structure, and health of plant communities in different regions and biomes. However, identifying vegetation in multi and hyperspectral images remains a difficult, time-consuming, and costly process. Traditional methods for vegetation mapping involve the in-terpretation of spectral indices such as the Normalized Difference Vegetation Index (NDVI), alt-hough they often suffer from limitations such as manual interpretation and limited spatial resolution of satellite images. Furthermore, machine learning techniques, artificial neural networks, decision trees, support vector machines, and random forests have shown promising results in identifying and classifying vegetation cover from hyperspectral images. However, due to the need for per-son-nel with specialized expertise, their application on a large scale is still challenging. On the other hand, correlation methods between curves have emerged as powerful and simplified tool for comparing spectral signatures of hyperspectral image pixels and efficiently classifying vegetation in a study area. Pearson's correlation coefficient and spectral angle mapper are among the most common correlation methods used in vegetation mapping. These correlation methods, among many others available, offer an easily implemented and computationally efficient approach, making them particularly useful for applications in developing countries or regions with limited resources. In this article, a comparative study of correlation/distance metrics was conducted for the detection of vegetation pixels in hyperspectral images. The study allowed for the comparison of five distance and/or correlation metrics: direct correlation, cosine similarity, normalized Euclidean distance, Bray-Curtis’s distance, and Pearson correlation. The two metrics that yielded the best accuracy results in vegetation pixel detection were direct correlation and Pearson correlation. Based on the selected methods, a vegetation detection algorithm was implemented and validated on a hyper-spectral image of the Manga neighborhood in Cartagena de Indias, Colombia. The spectral library was utilized for image processing, while the numpy and scipy libraries in the Python programming language were used for the mathematical calculation of correlations. Both the study's approach and the implemented algorithm aim to serve as a reference for conducting detection studies of various material types in hyperspectral images using open-access programming platforms.

Brucellosis infection induces fever, chills, sweats, headache, myalgia, arthralgia, anorexia, fa-tigue, and mood disorders. In mice, it causes a rise in IL-6, TNF-, and IFN-; and reduces sero-tonin and dopamine levels in hippocampus. There is loss in muscle strength and equilibrium and increased anxiety and hopelessness. Imipramine (ImiP) is a tricyclic antidepressant that increases the capacity of macrophages to destroy intracellular microorganisms in vivo. The effect of ImiP was evaluated in Balb/c mice infected with Brucella abortus 2308. Serum levels were determined in IFN-, IL-6, TNF-, IL-12, MCP-1, and IL-10 by FACS; the bacterial count in the spleen, by CFU; the serotonin concentration in the hippocampus, by HPLC; and strength, equilibrium, and mood by behavioral tests. Our results showed that infected vs. control mice had a significant rise in lev-els of IFN-, IL-6, TNF-, and IL-12 with a low IFN-/IL-6 ratio, elevated bacterial-counts, alter-ations in serotonin concentration at hippocampus, and decreased muscular strength, equilibrium, and mood. Infected mice treated with ImiP vs. infected mice showed: 1) improved mood; 2) in-creased hippocampal serotonin availability, splenic dendritic cells, and macrophage phagocytic activity; and 3) upturn inflammation and reduced CFU ability. Our results support that ImiP fa-vors positive outcomes in subjects handling Brucella infections likely by improving psychoim-mune resilience.

This work presents an application called APPMAR 1.0 based on Python ® environment, built to perform the downloading, treatment and analysis of meteorological and marine information. This application is composed of two main modules: the first module allows the downloading of information from the database (NOAA - WW3); the second module uses the principles of statistical mathematics for the treatment of waves and wind. The importance of this simple application is based on the free and agile access to meteorological and marine information for a coastal project. The determination of representative conditions of sea states ultimately will govern the process of design of coastal and oceanic infrastructure. The analysis of historical time series of local waves and winds allows the evaluation of average regimes or operational design, the ultimate limit states or extreme design, and the storms or design by persistence. In spite that the former analysis is a common task for coastal engineers, the codes generated are seldom shared for public use. In summary, for operational purposes is useful to have a freeware that can assist in the data processing for decision making and forcing of the mathematical models that are part of the common practice of coastal, oceanic and offshore engineering. This application has been tested in the Caribbean area of Colombia where meteorological and marine information are scarce.

The Chagas disease (CD) is an endemic infectious disease in a large part of Latin America. This disease is characterized by the fact of being caused by the parasite Trypanosoma cruzi. Some symptoms of this disease are cardiopathies and gastrointestinal problems. Therefore, the commonly used treatment consists of nitro drugs such as benznidazole and nifurtimox, which target the nitroreductase enzyme that docks to the coenzyme flavin mononucleotide (FMN) and an oxidation-reduction reaction is generated. From this reaction, the nitro chemical function of benznidazole and nifurtimox is reduced to amine. This amine in turn interacts with the parasite´s DNA. In vitro tests experimentally help in the study of the parasite resistance to the drug benznidazole. This fact could explain how nonsynonymous mutations in the nitroreductase (NTR) enzyme do not allow the anchorage of the FMN coenzyme and as a consequence the parasite susceptibility to benznidazole decreases as the drug cannot be reduced. The structural relations from the hybrid Quantum Mechanics-Molecular Mechanics (QM/MM) allow to detect the small changes generated in the system, considering a charge distribution associated with the structure, angle changes, interaction distances, potential surface calculations between the wildtype enzyme and the mutation found.

Background. Increasing evidence demonstrate that concentration of protein in infant formula >1.9g/100Kcal with high levels of insulinogenic aminoacids is associated with accelerated weight gain, increased fat mass accumulation and risk of adiposity. Purpose of this study was to conduct a systematic review to determine the metabolic effects in infants feed with infant formula optimized in protein. Methods. Systematic review was conducted according PRISMA Statement. RCTs with one intervention group (infant formula with 1.6-1.9gr of protein/100Kcal) and at least one comparative control group (infant formula with >1.9gr of protein/100Kcal) were included. Standardized mean differences (SMD), through random model were calculated. Results. 15 RCT were included. Optimized protein in infant formula was associated with less gain of BMI at 24 months of follow-up (SMD -0.25, IC95% -0.36 to -0.13, p 0.01) and less fat mass accumulation (SMD -0.68, IC95% -0.98 to -0.37, p 0.01). Optimized protein was also associated to less gain of weight, weight/age Z-score, weight/length Z-score, BUN (mmol/dL) and IGF1 (ng/ml). No effect on length/age Z-score was observed. Conclusions. Robust evidence showed optimized protein (1.6gr/100Kcal to 1.9gr/100Kcal) in infant formula is associated with metabolic benefits in infants with less weight gain, BMI and fat mass accumulation.

Power generation using renewable technologies has become a primordial option to satisfy the energy demand all over the world, being solar concentrating technologies widely applied for this purpose. A combination of Parabolic Trough Collector with Direct Steam Generation has been considered an excellent option for power generation, due to the economic cost and complexity in the plant are reduced. The thermal evaluation of the solar power plant as well as the PTC in the DSG process is very important in viability and economic analysis. In this sense, as the main objective of this work, a numerical tool for evaluating DSG with PTC technology has been developed. The software SOLEEC is a versatile, reliable, accurate and friendly to the user for thermally evaluating a DSG with PTC technology. The user has the possibility to compare the thermal behavior of different geometrical dimensions for a PTC; and even consider different materials; in order to satisfy the demand of superheated steam by a DSG process. The software has an error less than 5% when compared with literature results and in this paper is used to evaluate a power plant in Mexico obtaining that the change to DSG proposing different PTC could reduce the solar field about 35%.

The use of the voice of the customer as a main input to guide decision making towards customer centricity strategies has become a necessity for companies. This research proposes a structured method of textual processing using the KDD (Knowledge Discovery Databases) methodology applied to the tweets of users of Colombian public sector companies, through the analysis of temporal sentiments and topic modeling to identify the areas in which actions should be taken to improve the perception of service. To fulfill such purpose, tweets from January to June 2022 are processed, followed by a temporal analysis of the evolution of the sentiment based on 3 enriched dictionaries; after, the LDA (Linear Discriminant Analysis) algorithm is implemented to find the areas with ailment for the user, in addition to propose a method to homologate the CIER (Comisión de Integración Energética Regional) survey. Finally, metrics are detailed to follow up the perception of the service. It is concluded that for the Acueducto the topic with the highest number of complaints is related to "Water truck request", for Enel "Servide Outages" and for Vanti: " Case solution and request information". Also, the homologation of 3 of the 5 pillars on which the CIER survey is based is presented.

Purpose: This study aimed to determine the efficacy and safety of Oncoxin as an antitumoral supplement, and to describe its mechanism of action. Methods: We performed this scoping review according to the recommendations of the Joanna Briggs Institute and included patients older than 18 years-old who have any kind of tumor and receive Oncoxin as a supplement. We focused on the efficacy in terms of antitumoral properties, quality of life and survival, safety in terms of adverse events, and the mechanism of action. We did not limit for language or setting. We searched MEDLINE (Pubmed), EMBASE (Scopus), LILACS, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to nowadays. Results: We found a promising increment of survival when taking Oncoxin as a supplementary treatment. Additionally, the quality of life increased in terms of Karnofsky and EORTC scales. Regarding the mechanism of action, studies suggest it modifies inflammatory mediators’ expression, as evidenced by the reduction of COX-2, IL-1β, IL-6, TNF-α, IL-1β, IL-12, and IFN-γ. Besides, it promotes an arrest in the progression of cells from G1 into S, along with an increase in p27 and a decrease in cyclin D1 and pRb. Conclusions: We found promising complementary effects of Oncoxin to the standard treatment of cancer patients in diverse scenarios, with putative robust mechanisms of action. In addition to clinically relevant impacts verified in clinical trials, as well as it decreases the levels of pro-inflammatory cytokines, it can also decrease cytokines with antitumor activity such as IFN-γ, which should be further explored in larger trials and the long term.

Computer vision is a powerful technology that has enabled solutions in various fields by analyzing visual attributes in images. One field that has taken advantage of computer vision is agricultural automation, which promotes high-quality crop production. The nutritional status of a crop is a crucial factor in determining its productivity. This status is mediated by approximately 14 chemical elements acquired by the plant, and their determination plays a pivotal role in farm management. To address the timely identification of nutritional disorders, this study focuses on the classification of three levels of phosphorus deficiencies through individual leaf analysis. The methodological steps include: (1) generating a database with laboratory-grown maize plants that were induced to total phosphorus deficiency, medium deficiency, and total nutrition, using different capture devices; (2) processing the images with state-of-the-art transfer learning architectures (i.e. VGG16, ResNet50, GoogLeNet, DenseNet201, and MobileNetV2); and (3) evaluating the classification performance of the models using the created database. The results show that the VGG16 model achieves superior performance, with 98% classification accuracy. However, the other studied architectures also demonstrate competitive performance and are considered state-of-the-art automatic leaf deficiency detection tools. The proposed method can be a starting point to fine-tune machine vision-based solutions tailored for real-time monitoring of crop nutritional status.

The ciguatera is a food poisoning caused by the consumption of primarily coral fish; these species exist in large numbers in the seas that bathe the Colombian territory. The underreported diagnosis of this clinical entity has been widely highlighted due to multiple factors, as are among others, ignorance by the primary care practitioner consulted for this condition, clinical similarity with secondary gastroenteric symptoms, to common food poisonings of bacterial, parasitic or viral etiology. Eventually people affected by ciguatotoxin are related to trips to coastal areas hours before the onset of symptoms. Thanks to multiple studies over the years it has been possible to identify the relation of the dinoflagellates in the assembly of said toxin and its introduction into the food chain, starting by fish primarily inhabiting reef ecosystems and culminating in the intake of these by humans. Identifying the epidemiological link, its cardinal symptoms and affected systems such as gastrointestinal, peripheral nervous system and fortunately with a low frequency, the cardiovascular system, leads to a purely clinical diagnostic impression without further complementary studies, performing an adequate treatment primarily symptomatic without underestimating or overlooking any associated complications.

During the 16th and 17th centuries, Latin American cities adopted earthen construction techniques from European colonizers. As a result, rammed earth (RE) buildings now occupy an important place in Latin America's cultural heritage. However, earthquakes around the world have shown that unreinforced earthen constructions are highly vulnerable. For several years, researchers in northern South America have been proposing a technique that consists of installing confining steel plates (or wooden elements) on both sides of the RE walls forming a grid. This system has shown excellent performance in controlling seismic damage and increasing strength and ductility capacity. Although researchers have tested full-scale one- and two-story earthen walls under pseudo-static loading in the laboratory, and one- and two-story earthen walls at 1:1 and 1:2 scale on uniaxial and biaxial shaking tables, the behavior of a complete reinforced module (one- or two-story) on a shaking table has never been assessed. The present study presents the results of shaking table tests performed on two-story RE modules at 1:4 scale. The experimental data indicate that the retrofit system with confining steel strips was effective in reducing the seismic damage of earthen constructions. In addition, the comparison of the results of the 1:4 scale tests with the 1:2 and 1:1 scale tests previously conducted by the researchers, shows that the acceleration levels of the equivalent prototypes are in the same order of magnitude for the three scales.

We synthesized a small series of five 3-[4-arylmethoxy)phenyl]propanoic acids using an easy and short step synthetic route. All compounds were tested in vitro against a set of four protein targets identified as key elements in diabetes: GPR40, aldose reductase (AKR1B1), PPARγ and GLUT-4. Compound 1 displayed an EC₅₀ value of 0.075 μM against GPR40 and was an AKR1B1 inhibitor, showing IC₅₀ = 7.4 μM. Compounds 2 and 3 behave as AKR1B1 inhibitors, GPR40 agonists and showed an increase of 2 to 4-times in the mRNA expression of PPARγ, as well as the GLUT-4 levels. Docking studies were conducted in order to explain the polypharmacological mode of action and the interaction binding mode of the most active compounds on these targets. Compounds 1-3 were tested in vivo at 100 mg/kg dose, being 2 and 3 orally actives, reducing glucose levels in a non insulin-dependent diabetes mellitus mice model. Compounds 2 and 3 showed robust in vitro and in vivo efficacy, and could be considered as promising multitarget antidiabetic drug candidates. This is the first report of a single molecule with these four polypharmacological target action.

Currently, there are many studies on the application of nanotechnology in therapy. Metallic nanoparticles are promising nanomaterials in cancer therapy, however, functionalization of these nanoparticles with biomolecules has become relevant as their effect on cancer cells is con-siderably increased by photothermal and photodynamic therapy, drug nanocarriers, and speci-ficity by antibodies, resulting in new therapies that are more specific against different types of cancer. This review describes studies on the effect of functionalized palladium, gold, silver and platinum nanoparticles in the treatment of cancer.

Taeniid infections pose a significant threat to both animal and public health, as certain tapeworms within this group can also infect humans, potentially leading to severe health conditions. Therefore, this calls for preventive and control measures, such as regular deworming of dogs. While the efficacy of deworming has been established in developed countries, there is a paucity of reported deworming practices in rural areas of developing countries, such as Tanzania. This study aims to understand determinants for helminth treatment-seeking behavior towards control of cestodial taeniid infections in rural settings in northern Tanzania. A cross-sectional study was undertaken in agropastoral and pastoral areas of northern Tanzania. Comprehensive data from household surveys in selected sub-villages were collected to ascertain dog ownership, dog deworming practices, and the availability of dewormers. Analytical methods were employed to discern how various determinants influenced deworming practices among dog owners in these communities. Awareness of dewormers specifically formulated for dogs emerged as a pivotal factor affecting dog deworming practices. Dog owners who were informed about appropriate dog dewormers were nearly two times more likely to engage in deworming compared to those with limited knowledge (OR = 1.78, 95% CI 1.77 - 4.18, p < 0.001). A majority 32(51.6%, 95% CI: 38.7-64.3) acknowledged accessing dewormers for livestock within their wards. Praziquantel a potent dewormer on cestodes was least known to most dog owners 2(13%, 95% CI: 2.3-41.6). Praziquantel, a potent and common dewormer effective against cestodial taeniid infections, remains relatively unknown in rural areas of northern Tanzania. Therefore, more awareness on appropriate deworming agents against taeniids in dogs should be raised in rural dog-keeping communities.

The aim of this paper is to deep into the dynamic study of the well known Chebyshev-Halley family of iterative methods for solving nonlinear equations. Our objetives are twofold: one the one hand, we are interested in characterize the existence of extraneous attracting fixed points when the methods in the family are applied to polynomial equations. On the other hand, we are also interested in study the free critical points of the methods in the family, as a previous step to determine the existence of attracting cycles. In both cases, we want to identify situations where the methods in the family have a bad behavior from the root-finding point of view. Finally, and joining these two studies, we look for polynomials for which there are methods in the family where this two situations happen simultaneously. That is, the rational map obtained by applying a method in the Chebyshev-Halley family to a polynomial has both super-attracting extraneous fixed point and super-attracting cycles different to the roots of the polynomial.

This paper shows the firsts results of a methodological approach in which Remote Sensing technologies (Satellite imagery and LiDAR) combined with Least Cost Path algorithm on GIS are being tested like tools to overcome locally-based interpretations about populational patterns and communication routes during Flavian municipality in the Comarca de El Condado region. The identification of fourteen hypothetical communication routes between already known archaeological sites thanks to a recent archaeological prospection, and the confirmation of three sections of them and a new archaeological site demonstrate that the combined use of the aforementioned technics has a very useful to delve more deeply, more widely and at a variety of different scales into the relation between the twelve known/selected Early Roman Empire sites and the surrounding landscape in the right bank of Guadalén River. It is expected that, in next phases, this methodological approach will allow us to go deeper in analysing and understanding spatial distribution, exploitation, and interrelation between different Early Roman Empire sites, helping us to fill the aforementioned gaps in our understanding of the archaeological continuum in the region reducing time and costs.

The 32CA reactions of a series of pairs of bent three-atom-components (B-TACs) and linear TACs (L-TACs) towards electrophilic dicyanoethylene (DCE) have been studied within the Molecular Electron Density Theory in order to understand their different reactivity. ELF analysis indicates that while pseudodiradical B-TACs change their electronic structure to pseudoradical or carbenoid L-TACs upon dehydrogenation, zwitterionic B-TACs experience no remarkable change. Analysis of the CDFT indices indicates that five of the nine studied TACs have a strong nucleophilic character, thus participating in polar reactions towards electrophilic ethylenes. The activation energies of the 32CA reactions of the nine TACs towards electrophilic DCE range from 0.6 to 22.0 kcal·mol-1, which are by between 2.0 and 10.1 kcal·mol-1 lower than those involved in the non-polar 32CA reactions with ethylene. In general, B-TACs are more reactive than their L-TAC counterparts. A change of the regioselectivity is found in these polar 32CA reactions; in general, while B-TACs are meta regioselective, L-TACs are ortho regioselective. Analysis of the geometrical parameters indicates that at all TSs, the formation of the single bond involving the most electrophilic C4 carbon of DCE is more advanced than that involving the C5 one. A change of the asynchronicity in the reactions involving B-TACs and L-TACs is also found.

The obtention of simple formulae for the Lebesgue constants arising in the the classical Fourier series approximation is presented. Both even and odd cases are treated enlarging Fejér result. Asymptotic formulae are also obtained.

The relationship between Climate Change and Water is an obvious and key issue within the Sustainable Development Goals. This study aims to investigate the social representation created around this relationship in three different territorial contexts in order to evaluate the influence of the territory on the perception of the risk of Climate Change and its relationship with water. By means of a questionnaire completed by 1709 university students, the climatic literacy of the individual was evaluated in order to relate it to other dimensions on the relationship between Climate Change and Water (information, training previous on climate change and pro-environmental attitudes) in their different dimensions in three different territorial contexts. The results show that the socio-cultural context influences the social representation of Climate Change, but not from the climatological condition, so that it is reasonable to think that the social representation of this relationship is favoured by a common culture around this relationship.

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by Land Surface Phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources.

The electronic structure and the participation of the simplest azomethine imine (AI) in [3+2] cycloaddition (32CA) reactions have been analysed within the Molecular Electron Density Theory (MEDT) using DFT calculations at the MPWB1K/6-311G(d) level. Electron localisation function (ELF) topological analysis reveals that AI has a pseudoradical structure, while the conceptual DFT reactivity indices characterise this TAC as a moderate electrophile and a good nucleophile. The non-polar 32CA reaction of AI with ethylene takes place through a one-step mechanism with low activation energy, 5.3 kcal/mol-1. A bonding evolution theory (BET) study indicates that this reaction takes place through a non-concerted [2n+2τ] mechanism in which the C–C bond formation is clearly anticipated prior to the C–N one. On the other hand, the polar 32CA reaction of AI with dicyanoethylene takes place through a two-stage one-step mechanism. Now, the more favourable regioisomeric transition state structure (TS) is located 8.5 kcal•mol⁻¹ below the reagents, in complete agreement with the high polar character of the TS. The current MEDT study makes it possible to extend Domingo’s classification of 32CA reactions to a new pra-type of reactivity.

The Omicron variant of SARS-CoV-2 is the latest pandemic lineage causing COVID-19. Despite having a vaccination rate ≥ 85% Ecuador recorded a high incidence of Omicron from December 2021 to March 2022. Since Omicron emerged it is evolving into multiple sublineages with distinct prevalence in different regions. In this work, we use all Omicron sequences from Ecuador available at GISAID until March 2022 and the software Nextclade and Pangolin to identify which lineages circulate in this country. We detected 12 different sublineages (BA.1, BA.1.1, BA.1.1.1, BA.1.1.14, BA.1.1.2, BA.1.14, BA.1.15, BA.1.16, BA.1.17, BA.1.6, BA.2, BA.2.3), which has been reported in Africa, America, Europe, and Asia suggesting multiple introduction events. Sublineages BA.1.1 and BA.1 were the most prevalent. Genomic surveillance must continue to evaluate the dynamic of current sublineages, early introduction of new ones and vaccine efficacy against evolving SARS-CoV-2.

Since the mid-20th century, tourism has become a strategic activity for the economy of the Balearic Islands, causing profound social, territorial and environmental transformations. This fact challenges local society, which must be aware of its environment in order to better face the future challenges posed by this economic activity. With this goal, the official curriculum has been analyzed, making it possible to ascertain the approach with which this subject is taught by the administration and what objectives are set. Furthermore, a review was carried out of the contents of geography textbooks in the third year of ESO and the second year of Baccalaureate, which correspond to the educational stages in which tourism aspects appear. The results obtained represent a fundamental strategic diagnosis in order to improve the teaching and learning of this key activity for the Balearic Islands, giving it more importance and adapting its approach to the current times.

Since December 2019, the coronavirus disease (COVID-19) has rapidly spread worldwide. The Mexican government has implemented public safety measures to minimize the spread of the virus. In this paper, the authors use statistical models in two stages to estimate the total number of coronavirus (COVID-19) cases per day at the state and national level in Mexico. Two types of models are proposed: first, a polynomial model of the growth for the first part of the outbreak until the inflection point of the pandemic curve and then a second nonlinear growth model is used to estimate the middle and the end of the outbreak. Model selection will be performed using Vuong’s test. The proposed models show overall fit similar to predictive models (e.g. time series, and machine learning); however, the interpretation of parameters is less complex for decision-makers and the residuals follow the expected distribution when fitting the models without autocorrelation being an issue.

A plant’s health and productivity is influenced by its associated microbes. Although the common microbiome is often thought to be the most influential, significant numbers of rare or uncommon microbes (eg. specialized endosymbionts) may also play an important role in the health and productivity of certain plants in certain environments. To help identify rare/specialized bacteria and fungi in the most important angiosperm plants, we contrasted microbiomes of the shoots, roots and rhizospheres of Arabidopsis, Brachypodium, maize, wheat, sugarcane, rice, tomato, coffee, common bean, cassava, soybean, switchgrass, sunflower, Brachiaria, barley, sorghum, and pea. Plants were grown inside sealed jars on sterile sand or field soil. About 95% and 86% of fungal and bacterial diversity inside plants was uncommon, however judging by read abundance, up to half of the mycobiome consists of uncommon fungal cells, while less than 11% of bacterial endophytes are rare. Uncommon seed transmitted microbiomes consisted mostly of Proteobacteria, Firmicutes, Bacteriodetes, Ascomycetes and Basidiomycetes that most heavily colonized shoots, to a lesser extent roots and least of all rhizospheres. Soil served as a more diverse source of rare microbes than seeds, replacing or excluding the majority of the uncommon seed transmitted microbiome. With the rarest microbes, their colonization pattern could either be the result of stringent biotic filtering by most plants, or uneven/stochastic inoculum distribution in seeds or soil. Several strong plant-microbe associations were observed such as seed transmission to shoots, roots and/or rhizospheres of Sarocladium zeae (maize), Penicillium (pea and Phaseolus), and Curvularia (sugarcane), while robust bacterial colonization from cassava field soil occurred with the cyanobacteria Leptolyngbya into Arabidopsis and Panicum roots, and Streptomyces into cassava roots. Some abundant microbes such as Sakaguchia in rice shoots or Vermispora in Arabidopsis roots appeared in no other samples, suggesting they were infrequent, stochastically deposited propagules from either soil or seed (impossible to know based on the available data). Future experiments with culturing and cross inoculation of these microbes between plants may help us better understand host preferences and their role in plant productivity, perhaps leading to their use in crop microbiome engineering and enhancement of agricultural production.

Abstract: Understanding the reliability and sensitivity of jump testing is essential to determine the neuromuscular progress of athletes and make informed decisions. This study aimed to assess the reliability and sensitivity of countermovement jump (CMJ) and drop jump (DJ) tests metrics in female volleyball players. Sixteen semi-professional female volleyball players participated in the study. Intrasession and intersession reliability of CMJ and DJ metrics were evaluated using a randomized cross-over design. Dual force platform was used to collect data, and several dependent variables were calculated using forward dynamics. Intraclass correlation coefficients (ICC), coefficients of variation (CV) and minimum difference (MD) were calculated. The third attempt presented the highest values for both test, and changes in jump strategy in DJ. CMJ is consistent across sessions, while DJ also shows intersession differences (p<0.05) in 11 out of 15 variables. Most CMJ variables exhibit excellent reliability while DJ variables have lower reliability and higher variability. Concentric and eccentric impulses for DJ showed excellent reliability. Most CMJ variables showed excellent reliability and variability, DJ had lower reliability, higher variability, and lower sensitivity. These findings provide valuable information when assessing athletes' performance and highlight the reliability, sensitivity, and variability in jump performance for CMJ and DJ tests.

In a bid to resolve lingering problems in cosmology, more focus is being tilted towards cosmological models in which physical constants of nature are not necessarily real constants, but varying with cosmic time. In this paper we have study cosmology in nonlinear electrodynamics with the Newton's gravitational constant $G$ not a constant but vary in form of power-law of the scale factor of the universe. The evolution of the scale factor $a (t)$ is studied in this model which depends on nonlinear electrodynamics fine tuning term of $\alpha$. Then we check the stability of the model using the speed of sound.

Background: The febrile patient from tropical areas, in which emerging arboviruses are endemic, represent a diagnostic challenge and potential co-infections with other pathogens (i.e bacteria or parasites) are usually overlooked. Objectives: We present a case of an elderly woman diagnosed with dengue, chikungunya and Leptospira interrogans co-infection. Study Design: Case report. Results: An 87-year old woman from Colombia complained of upper abdominal pain, arthralgia, myalgia, hyporexia, malaise and intermittent fever accompanied with progressive jaundice. She had a medical history of chronic heart failure (Stage C, NYHA III), without documented cardiac murmurs, right bundle branch block, non-valvular atrial fibrillation, hypertension, and chronic venous disease. Her cardiac and pulmonary status quickly deteriorated after 24 hours of her admission without electrocardiographic changes and she required ventilatory and vasopressor support. In the next hours the patient evolved to pulseless electrical activity and then she died. Dengue IgM, NS1 ELISA, MAT for Leptospira interrogans and RT-PCR for chikungunya, were positive. Discussion: This case illustrates a multiple co-infection in a febrile patient from a tropical area of Latin America that evolved to death.

Purpose: Expanded carrier screening (ECS) informs couples of their risk of having offspring affected by certain genetic conditions. Limited data exists assessing the actions and reproductive outcomes of at-risk couples (ARCs). We describe the impact of ECS on planned and actual pregnancy management in the largest sample of ARCs studied to date. Methods: Couples who elected ECS and were found to be at high risk of having a pregnancy affected by at least one of 176 genetic conditions were invited to complete a survey about their actions and pregnancy management. Results: Three hundred ninety-one ARCs completed the survey. Among those screened before becoming pregnant, 77% planned or pursued actions to avoid having affected offspring. Among those screened during pregnancy, 37% elected prenatal diagnostic testing (PNDx) for that pregnancy. In subsequent pregnancies that occurred in both the preconception and prenatal screening groups, PNDx was pursued in 29%. The decision to decline PNDx was most frequently based on the fear of procedure-related miscarriage, as well as the belief that termination would not be pursued in the event of a positive diagnosis. Conclusions: ECS results impacted couples’ reproductive decision-making and led to altered pregnancy management that effectively eliminates the risk of having affected offspring.

This work presents the mathematical framework of the Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “2nd-CASAM-L”), which enables the most efficient computation of exactly obtained mathematical expressions of first- and second-order sensitivities of a generic system response with respect to functions (“features”) of model parameters. Subsequently, the first- and second-order sensitivities with respect to the model’s uncertain parameters, boundaries, and internal interfaces are obtained analytically and exactly, without needing large-scale computations. Within the 2nd-FASAM-L methodology, the number of large-scale computations is proportional to the number of model features (defined as functions of model parameters), as opposed to being proportional to the number of model parameters, which are considerably more than the number of features, being incomparably more efficient and more accurate than any other methods (statistical, finite differences, etc.) for computing exact expressions of response sensitivities (of any order) with respect to the model’s features and/or primary uncertain parameters, boundaries, and internal interfaces. The application of the 2nd-CASAM-L methodology is illustrated using a simplified energy-dependent neutron transport model of fundamental significance in nuclear reactor physics.

‘Arrayana’ mandarin fruits have a short postharvest life and are sensitive to chilling injury (CI) during cold storage. Brassinosteroids (BR) have been used as a sustainable technology to alleviate CI in fruits and improve postharvest quality. This study evaluated the effect of applying the 24-epibrasinolide analogue (EBR), at doses of 5 mg L-1; DI-31 analogue, at 5 and 10 mg L-1; and control, on the main physical and biochemical characteristics of 'Arrayana' mandarin stored at 4°C for 40 days and, subsequently, 7 days at room temperature (shelf life). The application of EBR and DI-31 analogues reduced the appearance of CI in the exocarp of 'Arrayana' mandarin fruits by reducing electrolyte leakage, maintaining membrane integrity, and increasing antioxidant activity and phenol content at the end of cold storage and shelf life. This was especially pronounced with 5 mg L-1 of EBR. Similarly, the BR maintained the postharvest quality of mandarins by reducing weight loss, respiratory intensity and chlorophyll degradation; increasing β-carotene; and maintaining titratable acidity, and soluble solids. Our research reports for the first time CI tolerance in Arrayana mandarin using natural (EBR) and spirostanic (DI-31), analogues and illustrates the tolerance functionality of the DI-31 analog on CI in fruit postharvest.

A tunable quantum cascade laser (QCL) spectrometer was used to develop methods for detecting and quantifying high explosives (HE) in soil based on multivariate analysis (MVA) and artificial intelligence (AI). For quantification, mixes of 2,4-dinitrotoluene (2,4-DNT) with concentrations from 0% to 20% w/w were investigated using three types of soils: bentonite, synthetic soil, and natural soil. A Partial least squares regression model was generated for predicting 2,4-DNT concentrations. To increase its selectivity, the model was trained and evaluated using additional analytes as interferences, including other HEs such as PETN, RDX, and TNT and non-explosives such as benzoic acid and ibuprofen. For detection, mixes of different explosives in soils were used to implement two AI strategies. In the first strategy, the spectra of the samples were compared with those of soils recorded in a database to identify the most similar soils based on QCL spectroscopy. Next, a Classical Least Squares preprocessing (Pre-CLS) was applied to soils spectra selected from the database. The parameter obtained based on the sum of the weights of Pre-CLS was then used to generate a simple binary discrimination model for distinguishing between contaminated and uncontaminated soils, achieving an accuracy of 0.877. In the second AI strategy, the same parameter was added to a principal component matrix obtained from spectral data of samples and used to generate multi-classification models based on different machine learning algorithms. A Random Forest model worked best with 0.997 accuracy and allowing to distinguish between soils contaminated with DNT, TNT, or RDX and uncontaminated soils.

Introduction: An epidemic of Coronavirus Disease 2019 (COVID-19) begun in December 2019 in China, causing a Public Health Emergency of International Concern. Among raised questions, clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews have been published on this matter. Methods: We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies, and also case reports, were included and analyzed separately. We performed a random-effects model meta-analysis to calculate the pooled prevalence and 95% confidence interval (95%CI). Results: 660 articles were retrieved (1/1/2020-2/23/2020). After screening by abstract/title, 27 articles were selected for full-text assessment. Of them, 19 were finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5-92.9%), cough (57.6%, 40.8-74.4%) and dyspnea (45.6%, 10.9-80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0-30.6%) required intensive care unit (ICU), with 32.8% presenting acute respiratory distress syndrome (ARDS) (95%CI 13.7-51.8), 6.2% (95%CI 3.1-9.3) with shock and 13.9% (95%CI 6.2-21.5%) of hospitalized patients with fatal outcomes (case fatality rate, CFR).Conclusion: COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and this group was associated with a CFR of over 13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure, and facilities to treat severe COVID-19.

Autonomous weapons systems (AWS), sometimes referred to as “killer robots”, are receiving evermore attention, both in public discourse as well as by scholars and policymakers. Much of this interest is connected with emerging ethical and legal problems linked to increasing autonomy in weapons systems, but there is a general underappreciation for the ways in which existing law might impact on these new technologies. In this paper, we argue that as AWS become more sophisticated and increasingly more capable than flesh-and-blood soldiers, it will increasingly be the case that such soldiers are “in the power” of those AWS which fight against them. This implies that such soldiers ought to be considered hors de combat, and not targeted. In arguing for this point, we draw out a broader conclusion regarding hors de combat status, namely that it must be viewed contextually, with close reference to the capabilities of combatants on both sides of any discreet engagement. Given this point, and the fact that AWS may come in many shapes and sizes, and can be made for many different missions, we argue that each particular AWS will likely need its own standard for when enemy soldiers are deemed hors de combat. We conclude by examining how these nuanced views of hors de combat status might impact on meaningful human control of AWS.

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (1st-CASAM-NODE)” which yields exact expressions for the first-order sensitivities of NODE decoder-responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim-Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, etc.). This work also lays the foundation for the ongoing work on conceiving the “Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-CASAM-NODE)” which aims at yielding exact expressions for the second-order sensitivities of NODE decoder-responses to the NODE parameters and initial conditions while enabling the most efficient computation of these sensitivities.

The role that aquatic aerosols might play in inter-ecosystem exchange in freshwater riparian environments has largely been understudied. In these environments, where freshwater streams are used both as drinking water and for treated waste disposal, water features like waterfalls, downed trees, and increased streamflow can serve as bioaerosol producers. Such water features could have an important role in the bacterial colonization of surrounding surfaces, including the riparian phyllosphere. In this study, we explore the influence of a freshwater stream’s bacterial community composition and micropollution on riparian maple leaves exposed to bioaerosols produced from the stream. Using culture-based and non-culture-based techniques, we compared phylloplane microbial communities in riparian zones, adjacent non-riparian forested zones, and the surface waters of the stream. In this system, riparian zone maple leaf surfaces had higher bacterial counts than non-riparian zone trees. Using metagenomic profiling of the 16S rRNA gene, we found that, while microbial communities on leaves in both riparian zone and forested sites were diverse, riparian zone bacterial communities were significantly more diverse. In addition, we found that riparian leaf bacterial communities shared more amplicon sequence variants (ASVs) with stream bacterial communities than forest leaves, indicating that the riparian zone phyllosphere is likely influenced by bioaerosols produced from water surfaces.

The UN’s 2030 Agenda brings new governance challenges to municipal environmental planning, both in large urban centres and in metropolitan peripheries. The opportunities of the new framework of action proposed by the United Nations (UN) and its integrative, global and transversal nature constitute advances from the previous models of municipal management based on the Local Agenda 21. This text provides evidence to apply quality criteria and validated instruments of participatory evaluation. These instruments have been built on the foundation of Evaluative Research, a scientific discipline that provides rigour and validity to those decisions adopted at a municipal level. A case study focused on a metropolitan area serves as a field of experimentation for this model of the modernization of environmental management structures at a local level. Details of the instruments, agents, priority decision areas, methodologies, participation processes and quality criteria are provided, as well as an empirically validated model for participatory municipal management based on action research processes and strategic planning that favours a shared responsibility across all social groups in the decision-making process and in the development of continuous improvement activities that are committed to sustainability. Finally, a critical comparison of weaknesses and strengths is included in light of the evidence collected.

The effect of individual and combined supplementation of FA and GPM on physiological variables, productive performance, and carcass characteristics of finishing pigs under heat stress conditions were investigated. Forty Yorkshire x Duroc pigs (80.23 kg) were individually housed and randomly distributed into 4 groups under a 2 x 2 factorial arrangement (n=10): Control (basal diet, BD); FA, BD + 25 mg FA; GPM, BD with 2.5% GPM; and MIX, BD with 25 mg FA and 2.5% GPM. Additives were supplemented for 31 days. The inclusion of FA or GPM did not modify rectal temperature and respiratory rate. An interaction effect (P &lt;0.05) was observed on FI, while average daily gain (ADG) and feed conversion (FC) were not affected by treatments (P &gt;0.05). The inclusion of FA improved hot and cold carcass weight and carcass yields, while the addition of GPM decreased the marbling (P &lt;0.05), and GPM tended to increase loin area (P &lt;0.10). GPM increased liver weight (p &lt;0.05). The addition of GPM and FA can improve some carcass characteristics under heat stress conditions. It is necessary to continue investigating different levels of inclusion of GPM and FA, to demonstrate their potential growth promoting effect in finishing pigs.

The Eurasian grapevine (Vitis vinifera L.) is the most widely grown horticultural crop in the world and is important for the economy of many countries. In the wine production chain, grape varieties play an important role as they directly influence the authenticity and classification of the product. Identifying the different grape varieties is therefore fundamental for quality control and inspection activities, as well as for regulating production. Currently, ampelography and molecular analysis are the main approaches to identifying grape varieties. However, both methods have limitations. Ampelography is subjective and prone to errors and is experiencing enormous difficulties as ampelographers are increasingly scarce. On the other hand, molecular analyses are very demanding in terms of cost and time. In this scenario, Deep Learning (DL) and Machine Learning (ML) methods have emerged as a classification alternative to deal with the scarcity of ampelographs and avoid molecular analyses. In this study, the most recent and current methods for identifying grapevine varieties using DL classification-based approaches are presented through a systematic literature review. The classification pipeline of the 31 studies found in the literature was described, highlighting its pros and cons. Most of the studies used DL-based models trained with leaf images acquired in a controlled environment at a maximum distance of 1.2 metres to classify grape varieties. In addition, there is a large gap between practical applications and the datasets used: a great lack of varieties, limited data acquired in the field and a lack of tests on plants under adverse conditions. Potential directions for improving this area of research were also presented.

A general framework for inference in dynamical systems is described, based on the language of Bayesian probability theory and making use of the maximum entropy principle. Taking as fundamental the concept of a path, the continuity equation and Cauchy's equation for fluid dynamics arise naturally, while the specific information about the system can be included using the Maximum Caliber (or maximum path entropy) principle.

The purpose of this study was to analyze the cross-linguistic influence of previously learned languages and working memory capacities on the vocabulary performance of two different typological languages. The objectives of this study were (1) to compare the working memory capacities of bilingual adults in relation to the vocabulary performance of two different languages never learned by the participants, and (2) to analyze to what extent the typology of previously learned languages influences working memory capaci-ties in relation to the vocabulary performance of French and Nahuatl. A group of 43 Mexican-Spanish college students participated in this experimental study. The participants completed a series of working memory tasks in Nahuatl and French. The results showed that working memory capacities were lower in Nahuatl than in French. Thus, a correlation was found between their first and second language and vo-cabulary performance in French. We can consider the influence of previously learned languages as a significant factor in vocabulary acquisition in accordance with the participants' working memory capacities.

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which yields best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally predicted posterior distribution of model results and calibrated model parameters. The 4th-BERRU-PM uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, thus incorporating, as particular cases, the results previously predicted by the second-order predictive modeling methodology 2nd-BERRU-PM, and vastly generalizing the results produced by extant data assimilation and data adjustment procedures. The 4th-BERRU-PM methodology encompasses the scopes of high-order sensitivity analysis (SA), uncertainty quantification (UQ), data assimilation (DA) and model calibration (MC). The application of the 4th-BERRU-PM methodology to energy systems is illustrated by means of the above-mentioned OECD/NEA reactor physics benchmark, which is modeled using the neutron transport Boltzmann equation involving 21976 imprecisely known parameters, the solution of which is representative of “large-scale computations.” The model result (“response”) of interest is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. Part 1 of this work illustrates the impact of high-order sensitivities, in conjunction with parameter standard deviations of various magnitudes, on the determination of the expected value and variance of the computed response in terms of the first four moments of the distribution of the uncertain model parameters. Part 2 of this work will illustrate the capabilities of the 4th-BERRU-PM methodology for combining computational and experimental information, up to and including forth-order sensitivities and distributional moments, for producing best-estimate values for the predicted responses and model parameters while reducing their accompanying uncertainties.

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

This paper proposes a novel data processing framework dedicated to bedload monitoring in underwater environments. After calibration, by integration the total energy in the nominal bandwidth, the proposed experimental setup is able to accurately measure the mass of individual sediments hitting the aluminum plate. This require a priori knowledge of the vibration trasients in order to match a predefined dictionary. Based on unsupervised hierarchical agglomeration of complex vibration spectra, the proposed algorithms allow to accurately localize the transients corresponding to the shocks created by sediment impacts on a steel plate.

The Independent Component Analysis (ICA) has been recently introduced as a reliable alternative to identify canonical scattering mechanisms within Polarimetric Synthetic Aperture Radar (PolSAR) images. This manuscript addresses two important aspects when applying such methods on real data, namely speckle filtering and statistical classification with ICA. A novel PolSAR data processing framework is introduced by adjusting the Lee's sigma filter to the particular nature of the Touzi's polarimetric decomposition. In its current form, it allows the use of the ICA mixing matrix in the derived speckle filter. An extension of the Fromont at al. iterative segmentation is introduced, equally. This proposed framework is tested using P band airborne PolSAR data acquired for the ESA campaign TropiSAR campaign.

The paper presents the results of the theoretical and practical research on developing the infrastructure for assessment of overall risk (explosion / occupational / terrorist attack) associated with unwanted events such as major accidents that can occur at explosive storehouses for civilian use. The scientific research outlined in this article was carried out within the Nucleu Project PN 16 43 02 15 - “Research on increasing safety levels at technical facilities for storage of explosives for civil use”.

Dengue is the most prevalent arthropod-borne disease globally and affects approximately 2.5 billion people living in over 100 countries. The increasing geographic expansion of Aedes aegypti mosquitoes which transmit the virus has made dengue fever a global health concern. There are currently no approved antivirals available to treat dengue, and the only approved vaccine used in some countries is limited to seropositive patients. Treatment of dengue therefore remains largely supportive to date; hence research efforts are being intensified for the development of antivirals against dengue. The NS3 and NS5 nonstructural proteins have been the major targets for dengue antiviral development due to their indispensable enzymatic and biological functions in the viral replication process. NS5 is the largest and most conserved nonstructural protein encoded by flaviviruses including dengue. Its multifunctionality makes it an attractive target for antiviral development against dengue, but research efforts are hindered due to its limited structural characterization compared to the NS5 of other flaviviruses like the Zika virus. Increase in structural insights into the dengue NS5 protein will accelerate drug discovery efforts focused on NS5 as an antiviral target. In this review, we will give an overview of the current state of therapeutic development against dengue.

The objective of this work was to evaluate the blending and grinding influence over the nutritional, sensorial and sustainable aspects of coffee. To do so, a systematic review of the literature was accomplished. The database for the selection of relevant papers was the Portal de Periódicos da Capes, with remote access via CAFe. For the elaboration of the research, a chronological criterion with period restriction was used, considering the period between 2008-2022, to access all possible works related to the theme of this work. The following terms were used: blending; grinding; coffee; nutrition-al; sensorial; sustainability. To filter the searches, the association of these terms was also used by means of links and word associations. In the terminology, the Boolean operator AND was used to interconnect the terms used. Roasting degree, grinding, and amount of each coffee species impacts the nutritional and sensorial aspects of coffee. And the determination of each blending influences the sustainability of the environment, economic and social aspects of the coffee chain.

Existing studies provide evidence that buildings and the construction sector are the largest consumers of natural resources and carry the greatest responsibility for greenhouse gas emissions. In order to reverse this situation, future challenges involve utilising the least resources possible. To this end, building refurbishment becomes a crucial strategy given its potential to improve operational energy efficiency and to extend the life span of existing building stock, thereby reducing the environmental impact while also providing social and economic benefits to our cities. Life Cycle Sustainability Assessment (LCSA) has become one of the scientific community’s most widely recognised methodologies for the evaluation of the social, economic, and environmental dimensions (Triple Bottom Line), since it assesses sustainability using quantitative metrics. However, the implementation of this methodology to support the refurbishment process at the project stage in building design tools, such as BIM, remains scarce. One of the main obstacles lies in the difficulties of accessing the building information, given that the system boundaries only cover new materials and products. Hence, this study proposes a BIM plug-in development to support the multi-dimensional building material selection in the early design steps based on the LCSA of a building during the refurbishment stage and validates its application in a case study. The results show the viability of using this tool during the early design stages and demonstrate the consistency of the results to evaluate various material and product alternatives for the refurbishment of the envelope system of a multi-family residential building. This study contributes towards the integration of decision-making by providing real-time assessment of the building envelope.

The [3+2] cycloaddition (32CA) reactions of strongly nucleophilic norbornadiene (NBD) with simplest diazoalkane (DAA) and three DAAs of increased electrophilicity have been studied within the Molecular Electron Density Theory (MEDT) at the MPWB1K/6-311G(d,p) computational level. These pmr-type 32CA reactions follow an asynchronous one-step mechanism with activation enthalpies ranging from 17.7 to 27.9 kcal·mol-1 in acetonitrile. The high exergonic character of these reactions makes them irreversible. The presence of electron-withdrawing (EW) substituents in the DAA increases the activation enthalpies, in complete agreement with the experimental slowing-down of the reactions, but contrary to the Conceptual DFT prediction. Despite the nucleophilic and electrophilic character of the reagents, the global electron density transfer at the TSs indicates rather non-polar 32CA reactions. The present MEDT study allows establishing that the depopulation of the NNC core in this series of DAAs with the increase of the EW character of the substituents present at the carbon center is responsible for the experimentally found deceleration.

The regioselectivity in non-polar [3+2] cycloaddition (32CA) reactions has been studied within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) level. To this end, the 32CA reactions of nine simplest three-atom-components (TACs) with 2-methylpropane were selected. The electronic structure of the reagents has been characterised through the Electron Localisation Function (ELF) and the Conceptual DFT. The energy profiles of the two regioisomeric reaction paths and ELF of the transition state structures are studied to understand the origin of the regioselectivity in these 32CA reactions. This MEDT study permits to conclude that the least electronegative ends X1 atom of these TACs controls the asynchronicity in the C-X (X = C,N,O) single bond formation, and consequently, the regioselectivity. This behaviour is a consequence of the fact that the creation of the non-bonding electron density required for the formation of the new CX single bonds has a lesser energetic cost at the least electronegative X1 atom than that at the Z3 one.

The durability of bridge decks is a critical factor in ensuring the safety and longevity of transportation infrastructure. This article explores advanced materials and innovative techniques designed to mitigate cracking in bridge decks, a common issue that can compromise structural integrity and increase maintenance costs. It provides a comprehensive review of cutting-edge solutions such as Fiber-Reinforced Polymers (FRP), High-Performance Concrete (HPC), Ultra-High Performance Concrete (UHPC), and self-healing concrete technologies. Each material is analyzed for its ability to enhance strength, reduce permeability, and improve resistance to environmental stressors. Additionally, the article examines the role of surface treatments, sealants, and routine maintenance practices in prolonging the life of bridge decks. By synthesizing current research and practical applications, this article offers valuable insights and recommendations for engineers, contractors, and policymakers seeking to advance bridge deck durability through innovative materials and methodologies.

The rapid ageing of populations around the World is creating complex challenges for national governments. The establishment of sustainable and equitable long-term care systems for old and dependent people is one of the main issues of social policy in developed countries. The aim of this work is to define a cost model for residential and day care centres for dependent persons in Cantabria (Spain). The cost model will make it possible to establish the theoretical cost of attending to the needs of the different types of dependent persons in the different types of care centres, and the methodology used could be extrapolated to other regions. The daily cost per user for elderly residential care is €53.72. The cost per user in elderly day centres (5 days) is 32.56 euros. In residential centres for people with disabilities, the values range between €47.41 and €75.25 depending on the category of the centre. In three categories of centres the public price is not enough to cover the cost (physical disability, intellectual disability, mental illness – low care), and therefore the administration should reconsider their public prices for these kind of centres if they want to really contribute to the sustainability of these residential care centres. This research will have important implications for policy-makers in a context of fulfilment of SDGs and where better support for old and disabled people and their carers, as well as fair and efficient financing of social care services, are essential to address the current and future challenges of dependency.

Humanity, culture, societal development and language issues are mutually reinforcing much as they are intricately interwoven in a non-ceasing dynamic interrelationships within the matrix defined by language standardization or development, acquisition and use that mostly take up central place as unifying and propelling forces in language discourse. Within the confines of globalization which is neither homogenization nor convergence; but the beginning of drawing on the strength of indigenous capabilities to create knowledge ecology that would enliven socio-economic and scientific development of the world in far reaching interconnectivities and relationships across every clime, issues pertaining to language development, acquisition and use become imperative. It is against this background that this paper examines the development/standardization, acquisition and use of Esan language as one of several Nigerian indigenous languages to promote scientific and technological development through knowledge creation, preservation and dissemination. The obsession of using western model and epistemological outlook to achieve appropriate scientific and technological development to the utter neglect of home grown and culturally distilled efforts were also examined. In the light of the dare consequences and the harsh conditions globalization imposes on developing nations, this paper highlights standardization and use of indigenous languages in chatting appropriate trajectory for effectual developmental efforts in fast shrinking contemporary world.

Placenta accreta spectrum (PAS) disorders are characterized by abnormal trophoblastic invasion into the myometrium, leading to significant maternal health risks. PAS includes placenta accreta (invasion &lt;50% of the myometrium), increta (invasion &gt;50%), and percreta (invasion through the entire myometrium). The condition is most associated with previous cesarean deliveries, and its incidence increases with the number of cesareans. Other risk factors include advanced maternal age, multiparity, and various uterine surgeries. The increasing global cesarean rates heighten the importance of early PAS diagnosis and management. The study reviewed molecular mechanisms driving PAS, focusing on signaling pathways, genetic expression, biomarkers, and non-coding RNAs involved in trophoblastic invasion. It explored genetic expression and key regulatory processes such as apoptosis, cell proliferation, invasion, and inflammation. The manuscript was compiled from recent scientific literature (2014 – 2024) from the Scopus, PubMed, Google Scholar, and Web of Science databases. Placenta Acreta Spectrum; acreta; increta; percreta; trophoblast invasion; miRNAs, lncRNAs; genetic expression; biomarkers; signaling pathways were the employed keywords to compile relevant literature. The PAS is an important obstetric health problem that challenges maternal health risks associated with abnormal trophoblastic invasion that relies on abnormal placentation, uterine scarring, and impaired decidualization. Identifying new biomarkers like AFP, sFlt-1, β-hCG, PlGF, and PAPP-A aids early detection and management. Understanding genetic expression and non-coding RNAs is crucial for unraveling PAS complexities. Besides, aberrant signaling pathways like Notch, PI3K/Akt, STAT3, and TGF-β offer potential therapeutic targets to modulate trophoblastic invasion. This review underscores the need for interdisciplinary care, early diagnosis, and ongoing research into PAS biomarkers and molecular mechanisms to improve prognosis and quality of life for affected women.

We are living in a business context characterized by change, which today behaves with an unprecedented intensity, driven by the technological revolution and increased competition. As a result, increasingly large and complex companies are facing profound transformation processes in which the role of the human factor and of managers in particular, due to their high capacity to impact the organization, is essential. In response to this reality, the literature has developed a large number of approaches from different areas of knowledge: from business economics to psychology, including technical disciplines. This article offers a classification of these approaches that provides an overview of research on the role of managers in change management.

The intramolecular ionic Diel-Alder (IIDA) reactions of two dieniminiums have been studied within the Molecular Electron Density Theory (MEDT) at the B97XD/6-311G(d,p) computational level. ELF topological analysis of dieniminiums shows that its electronic structure can been seen as the sum of those of butadiene and ethaniminium. The superelectrophilic character of dieniminiums accounts for the high intramolecular global electron density transfer taking place between the diene and iminium frameworks at the transition state structures (TSs) of these IIDA reactions. The activation enthalpy associated to the IIDA reaction of the experimental dieniminium, 8.7 kcal·mol-1, is closer to that of the ionic Diels-Alder (I-DA) reaction between butadiene and ethaniminium, 9.3 kcal·mol-1. However, the activation Gibbs free energy of the IIDA reaction is 12.7 kcal·mol-1 lower than that of the intermolecular I-DA reaction. The strong exergonic character of the IIDA reaction, higher than 17 kcal·mol-1, makes the reaction irreversible. These IIDA reactions present a total re/exo and si/endo diastereoselectivity, which is controlled by the most favourable chair conformation of the tetramethylene chain. Electron localization function (ELF) topological analysis of the single bond formation indicates that these IIDA reactions take place through a non-concerted two-stage one-step mechanism. Finally, ELF and atoms-in-molecules (AIM) topological analyses of the TS associated to inter and intramolecular processes show the great similitude among them.

The ionic Diels-Alder (I-DA) reactions of a series of six iminium cations with cyclopentadiene have been studied within the Molecular Electron Density Theory (MEDT). The superelectrophilic character of iminium cations,  > 8.20 eV, accounts for the high reactivity of these species participating in I-DA reactions. The activation energies are found between 13 and 20 kcal·mol-1 lower in energy than those associated to the corresponding Diels-Alder (DA) reactions of neutral imines. These reactions are low endo selective as a consequence of the cationic character of the TSs, but highly regioselective. Solvents have poor effects on the relative energies, and an unappreciable effect in the geometries. In dichloromethane the activation energies increase slightly as a consequence of the better solvation of the iminium cations than the cationic TSs. ELF topological analysis of the bonding changes along the I-DA reactions shows that they are very similar to those in polar DA reactions. The present MEDT study makes it possible establishing that the global electron density transfer (GEDT) taking place at the TSs of I-DA reactions, and not steric (Pauli) repulsions such as have been recently proposed, are responsible for the features of these type of DA reactions.

Speech signals are degraded in real-life environments, product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One of the conditions that make adverse quality difficult to handle in those systems is reverberation, produced by sound wave reflections that travel from the source to the microphone in multiple directions.To enhance signals in such adverse conditions, several deep learning-based methods have been proposed and proven to be effective. Recently, recurrent neural networks, especially those with long and short-term memory (LSTM), have presented surprising results in tasks related to time-dependent processing of signals, such as speech. One of the most challenging aspects of LSTM networks is the high computational cost of the training procedure, which has limited extended experimentation in several cases. In this work, we present a proposal to evaluate the hybrid models of neural networks to learn different reverberation conditions without any previous information. The results show that some combination of LSTM and perceptron layers produce good results in comparison to those from pure LSTM networks, given a fixed number of layers. The evaluation has been made based on quality measurements of the signal's spectrum, training time of the networks and statistical validation of results. Results help to affirm the fact that hybrid networks represent an important solution for speech signal enhancement, with advantages in efficiency, but without a significan drop in quality.

Player’s performance in an intense sport such as basketball is known to be related to attributes like speed, agility, and power. This study presents a comparative analysis of associations between anthropometric assessment and physical performance in different age-group elite youth basketball players, while simultaneously identifying the predictors for speed and agility in these players. U14 (n=44), U15 (n=45) and U16 (n=51) players were tested for anthropometry, lower body power, speed, and agility. U16 players were found to be taller, heavier, more muscular than U14 and U15 players. Also, the U16 group showed better performance in all performance tests. Age had a significant positive correlation with countermovement (CMJ) and drop jump (DJ) performance in U14 players, and a significant negative correlation with 10m and 20m sprint times in U15 group. CMJ and DJ emerged as the most significant predictors for sprint and agility variables, respectively. Body fat percentage was found to be a significant predictor for the speed and agility tests in all age groups, but a negative lower-body power predictor. Therefore, besides all sport-specific and fitness tests, it is essential to place emphasis on the percentage of body fat when designing players’ individualized training programs, and during team selection.

Background: As noninvasive prenatal screening usage grows in the general obstetrics setting, proper patient education on the screen’s benefits and limitations is needed. Objective: Describe the use of a technology platform designed for large-scale dissemination of noninvasive prenatal screening information and results. Study Design: The technology platform functioned as follows: Patients were emailed a link to an noninvasive prenatal screening general-education video upon laboratory receipt of a test requisition. Providers were then notified upon availability of patients’ results. If noninvasive prenatal screening results were negative, the patient was sent an automated email with instructions to access results through a secure portal where she could watch tailored informational videos, request “on-demand” or scheduled genetic counseling, or decline any further services. If genetic counseling was elected, a summary of the session was sent to the ordering provider and patient upon completion. If noninvasive prenatal screening results were positive, either the ordering provider or a board-certified genetic counselor contacted the patient directly to communicate test results and provide counseling. The number and type of results issued through the platform, the number and type of genetic counseling consultations completed, and factors associated with requesting laboratory-delivered genetic counseling were tracked and analyzed for a 39-month period. Results: Over the study period, 67,122 noninvasive prenatal screening results were issued through the platform, and 4,673 patients elected genetic counseling consultations; 95.2% (n=4,450) of consultations were for patients receiving negative results. Over 70% (n= 3,370) of consultations were on-demand rather than scheduled. Median consultation time was 14 minutes for positive results and six minutes for negative results. A positive screen, advanced maternal age, family history, previous history of a pregnancy with a chromosomal abnormality, and other high-risk pregnancy were associated with the greatest odds of electing laboratory-delivered genetic counseling. Conclusions: By combining web education, automated notifications, and genetic counseling, we implemented a service that effectively facilitates results disclosure for ordering providers. These data demonstrate the capability to deliver noninvasive prenatal screening results, education, and counseling—congruent with management guidelines—to a large population, which is imperative to quality care as uptake increases.

This paper presents a new methodology that provides the analysis of surface texture changes in areas adjacent to the volcano and its impact product of volcanic activity. To do this, algorithms from digital image processing such as the co-occurrence matrix and the wavelet transform are used. These methods are working on images taken by the Landsat satellite platform sensor 5 TM and Landsat 7 ETM + sensor, and implemented with the purpose of evaluating superficial changes that can warn of surface movements of the volcano. The results were evaluated by similarity metrics for grayscale images, and validated in two different scenarios that have the same type of eruption, but differ, essentially, in climate and vegetation. Finally, the proposed algorithm is presented, setting the parameters and constraints for implementation and use.

Brugada Syndrome is a cardiac channelopathy closely related to lethal arrhythmias and sudden death in people without underlying structural pathology. The diagnosis is usually assumed with electrocardiographic patterns strictly limited to the right precordial leads, V1 or V2; but this is not so at all. In our article, we describe the clinical case of a patient with a novel and different electrocardiographic presentation: the typical diagnostic pattern was presented in a lower lead of the electrocardiogram, and next to it, another pattern was presented in a contiguous lead. In addition, we propose the possible association of a structural pathology (non-compaction cardiomyopathy) with Brugada Syndrome, since both share a possible common genetic origin in the SCN5A gene.

Gestational diabetes mellitus (GDM) is a hyperglycemia state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, poorly reproducible, and tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to get a result. Near-infrared (NIR) spectroscopy, a simple, fast and low-cost analytical technique has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and time of analysis. Serum samples from the first (before GDM diagnosis) and the second (at the time of GDM diagnosis) trimester of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best first and second trimester models got areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR spectroscopy-based methods for the prediction of GDM. The developed methods allow to predict GDM from 10 µL of serum in only 32 minutes. They are simple and fast, and have a great potential to be applied in clinical practice, especially as alternative screening tools to the OGTT at the time of GDM diagnosis.

Interdisciplinary STEM and STEAM education give us an opportunity for creativity and educational innovation in a world scenario that needs training in which students can achieve all educational objectives and are prepared to achieve sustainable development. The rural environment with its land is a scenario that provides us with a range of educational resources for the development of STEM and STEAM projects in which students who are better trained and prepared for the needs of today's world are developed, as well as students who are more linked and sensitized to the environment, with the rural environment and its land, so important in our time.  In this article, we will collect examples from Latin America; STEM projects are being developed in which young people establish links with their environment, territory, and the local environment surrounding them. We must look carefully at projects and works in which students' ties with their land and environment are valued through the STEM and STEAM education necessary today. In this scenario, a comparison has been made between Latin American countries and Spain.

The latest World Atlas of Desertification represents a turning point in the diagnosis of desertification. While it forgoes desertification mapping due to the intrinsic complexity of the phenomenon and the impossibility of measuring it using a single indicator, it introduces the Convergence of Evidence paradigm, which identifies socioeconomic and biophysical variables whose behavior allows pointing out those areas prone to desertification. The Spanish National Action Program Against Desertification (PAND), back to 2008, already implemented a similar approach to identify five “desertification landscapes” within Spain using both socio-economic and climatic information. The PAND was not only pioneering but also, unfortunately, accurate. Desertification in Spain has continued to worsen and the first two decades of the 21st century have consolidated an agri-food model whose dynamics have exacerbated the desertification processes identified in the PAND. Despite its scientific value, the PAND lacked a proper action plan and was completely detached from the diagnosis. As a result the diagnosis it provided was not followed by effective actions to halt desertification in Spain. The Spanish Government's recent declaration of climate and environmental emergency requires a new strategy to combat desertification. This commitment is an excellent opportunity to update the diagnosis of the situation and, more crucially, to unify the different desertification sectoral policies and actions under a single front. We provide here elements for a roadmap to be designed around the pressures, impacts, and drivers that define today's Spanish desertification landscapes to manage them effectively and avoid their further degradation.

Background: The use of complementary therapies in the population is increasing, so it is necessary to understand the training that health professionals receive in this type of therapy in their training plans, as they are often the primary source of information for patients. Our objective was to investigate Spanish universities that offer subjects on complementary therapies in their Nursing degree programs. Methods: Observational descriptive cross-sectional study. For this purpose, we used the document published on the website of the Ministry of Universities as a working document. Additionally, a literature search was conducted up to September 2023 in the PubMed database, along with reverse searches. Results: Out of a total of 62 universities, only 16 (29%) offer a subject related to this type of therapy, with most of them being elective courses. Conclusions: The training content on complementary care in Nursing degree programs in Spanish universities is scarce, highlighting the potential benefit of expanding and promoting it, in line with the recommendations of the World Health Organization.

This paper presents performed Ansys numerical simulation on WindFloat structures. It contributes to the methodology of calculation based on CFD instruments to study the movements of the waves on semi-submersible stationary structures and highlights the importance of using RAO functions. RAO numerical approach developed can be applied to design semisubmersible WindFloat structures in order to fulfill essential requirements regarding operational safety and design. Numerical methodology was designed in accordance marine loads and the I.T.T.C. recommendations. The numerical RAO results for regular wave movements include many elements for the semi-submergible structure. Close results to open sea operation can be achieved by constant improvement in numerical simulation methodologies. The work opens the way for further hydrodynamic development on irregular waves for realistic hydrodynamic and structural response of the actual semi-submersibles at sea. The results demonstrate the accuracy of RAO function approach for specific WindFloat in Jonswap spectrum.

Daptomycin is one of the last therapeutic resources for multidrug-resistant gram- positive bacteria. Despite its structural similarities with glycopeptides, its mechanisms of action and resistance are different, and in some respects are not completely understood. Mutations in several genes have been associated to daptomycin resistance, especially in mprF, walkR, rpoB and rpoC, but their role and importance remain to be elucidated. We have studied mutations in 11 genes, which have been previously associated to daptomycin non- susceptibility, in 9 daptomycin non-susceptible Staphylococcus aureus clinical isolates (daptomycin MIC: > 1mg/L). Susceptibility to daptomycin, vancomycin, linezolid, oxacillin, telavancin and dalbavancin were studied. walkR, agrA, cls1, cls2, fakA, pnpA, clpP, prs, rpoB, rpoC and mprF were amplified by PCR and sequenced. The sequences were compared with the S. aureus ATCC 25923 complete genome (GenBank gi: 685631213) by using BLAST® software. We did not find any changes in walkR, pnpA, prs and clpP. All isolates excepting isolate 5 showed a high number of significant mutations (between 13 and 25 amino acid changes) in mprF. Most isolates also showed mutations in rpo genes, cls genes and fakA. Daptomycin non-susceptibility in S. aureus clinical isolates seems to be reached through different mutations combinations when compared to S. aureus ATCC 25293. Especially mprF and cls1 showed a very high polymorphism in most isolates. Meanwhile, one isolate, St5, showed only single mutation in mprF (P314T).

This paper shows the proposal of the use of linked data for smart metering systems. The aim of linked data in smart grid applications such as smart metering systems is to give semantic knowledge of the energy transactions between all participators in the power markets. In combination with other technologies like blockchain, the linked data could improve decentralization and security in the world's energetic future.

Abstract: Abstract: The objective of this article is to analyze the dimensions of creativity concerning students with high abilities. Firstly a review of the most relevant scientific contributions on creativity is carried out. Next the dimensions of creativity in secondary school students who have been previously identified as high- ability students are analyzed. Those abilities associated to di-vergent thinking were assessed by means of the Torrance Test of Creative Thinking [19]. The flu-ency, flexibility and originality dimensions were assessed with the Scientific-Creative Thinking Test (TPCC, [7]). The results obtained evidence that high-ability students achieve greater scores in both the figurative creativity and scientific-creativity dimensions. A significant relationship between creativity and high ability can therefore be established. This study is of an exploratory nature and the results obtained contribute to develop future studies in application of its findings in the teaching-learning process..

High efficiency and safety are critical factors in ensuring optimal performance and reliability of systems and equipment across various industries. Fault Monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring system performance and identifying the presence of faults or abnormalities. However, traditional FM methods face limitations in fully capturing the complex interactions within a system and providing real-time monitoring capabilities. To overcome these challenges, Digital Twin (DT) technology has emerged as a promising solution to enhance existing FM practices. By creating a virtual replica or digital copy of a physical equipment or system, DT offers the potential to revolutionize fault monitoring approaches. This paper aims to explore and discuss the diverse range of predictive methods utilized in DT and their implementations in FM across industries. Furthermore, it will showcase successful implementations of DT in FM across a wide array of industries, including manufacturing, energy, transportation, and healthcare The utilization of DT in FM enables a comprehensive understanding of system behavior and performance by leveraging real-time data, advanced analytics, and machine learning algorithms. By integrating physical and virtual components, DT facilitates the monitoring and prediction of faults, providing valuable insights into the system’s health and enabling proactive maintenance and decision-making.

This work continues the review and illustrative application to energy systems of the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” (4th-BERRU-PM) methodology. The 4th-BERRU-PM methodology uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, in-cluding fourth (and higher) order sensitivities of computed model responses with respect to model parameters. The 4th-BERRU-PM methodology yields the fourth-order MaxEnt posterior distribution of experimentally measured and computed model responses and parameters, in the combined phase-space of model responses and parameters. The 4th-BERRU-PM methodology encompasses fourth-order sensitivity analysis (SA) and uncertainty quantification (UQ), which were reviewed in the accompanying work (Part 1), as well as fourth-order data assimilation (DA) and model calibration (MC) capabilities, which will be reviewed and illustrated in this work (Part 2). The applicability of the 4th-BERRU-PM methodology to energy systems is illustrated by using the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark, which is modeled using the linear neutron transport Boltzmann equation, involving 21976 im-precisely known parameters. This benchmark is representative of “large-scale computations” such as those involved in the modeling of energy systems. The result (“response”) of interest for the PERP benchmark is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. The impact of the high-order sensitivities of the response with respect to the PERP model parameters is quantified for “high-precision” parameters (2% standard deviations) and “medium-precision” parameters (5% standard deviations). Analyzing the best-estimate results with reduced uncertainties for the 1st- through 4th-order moments (mean values, covariance, skewness, and kurtosis) produced by the 4th-BERRU-PM methodology for the PERP benchmark indicates that, even for systems mod-eled by linear equations (e.g., the PERP benchmark), retaining only first-order sensitivities is insufficient for reliable predictive modeling (including SA, UQ, DA, MC). At least second-order sensitivities should be retained in order to obtain reliable predictions.

Keywords: emerging pollutants; pharmaceuticals; plant uptake; soil behavior; soil remediation.

: BACKGROUND: The prevalence of smoking among students is a growing concern, particular-ly among medical students. Being associated with stress, competitiveness, and various social in-fluences, smoking can have detrimental effects on self-esteem and self-efficacy and may create a vicious cycle that may contribute to students’ well-being and academic performance out-comes.METHODS: A cross-sectional study on 456 medical students was conducted via an online survey using structured questionnaires on socio-demographic characteristics, smoking habits, nicotine dependence, self-esteem, and self-efficacy. RESULTS: The prevalence of smoking was 31.1% The scores of self-esteem and self-efficacy were positively correlated with smoking habits (W1=0.957, W2=0.975, P<0.05). Students presented rather low smoking addiction with male stu-dents having slightly higher scores than female students on self-esteem and self-efficacy, mili-tary students had higher self-esteem scores than civilians with physical activity having a posi-tive correlation with non-smoking behavior. CONCLUSION: According to our results, self-esteem and self-efficacy were slightly positively correlated with smoking habits. Furthermore, there was no statistically significant association between other social factors and smoking. Our results may develop a theoretical basis for medical students’ psychological variables studying for further implementation of university educational programs and preventive interventions em-powering students towards an overall better quality of life, addressing, among others, smoking behaviors.

Diets that restrict the amount of carbohydrates positively affect markers related to metabolic syndrome (MS). However, completely carbohydrate-free diets have been studied in lesser extent, being their effect on biochemical and morphometric parameters in a rat model of MS the main objective of this study. MS was induced by a high-glucose diet for 20 weeks in male Wistar rats with a subsequent exposition to an essentially carbohydrate-free diet (CFD) for 20 weeks. Daily measurements of food consumption and monthly measurements of body weight were made. At week 40, glucose, insulin, lipid profile, ketone bodies, C-reactive protein (CRP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), urea, creatinine, liver and muscle glycogen, and serum, hepatic, renal and pancreatic malondialdehyde (MDA) were assessed. Exposition to CFD showed decrease in caloric intake and body weight. Likewise, the group showed normalization in liver and serum MDA parameters, insulin, lipid profile, ALT, liver glycogen, and creatinine. The CFD decreased glucose concentration and the inflammatory state, also, increased the concentration of ketone bodies and urea. The change towards CFD reverses the metabolic alterations generated with MS except for glycemia and uremia, probably due to the high rate of gluconeogenesis generated by the high protein content in the diet.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

This study is focused to the aquatic environments of the Sian Ka’an reserve, a World Heritage Site. We applied protocols recently developed for the rapid assessment of most animal taxa inhabiting any freshwater system, by using light traps, and DNA barcodes, represented by the mitochondrial gene Cytochrome Oxidase I (COI). We DNA barcoded 1037 specimens of mites, crustaceans, insects, and fish larvae from 13 aquatic environments close or inside the reserve, with a success rate of 99.8%. In total, 167 Molecular Operational Taxonomic Units (MOTU’s) were detected. From them we identified 43 species. All others remain as a MOTU. For analyzing the adult fish communities, we applied the non-invasive method of environmental DNA (eDNA), and identified the sequences obtained with the Barcode of Life Database (BOLD). We found 25 fish species, and other terrestrial vertebrates from this region. No alien species was found. After a comparison of the MOTU’s from all systems, we found that each water body was unique respect the communities observed. The reference library presented here represents the first step for future programs to detect any change in these ecosystems, including invasive species, or improve knowledge of freshwater zooplankton, because most of the MOTU’s are possibly new species to science.

Vertical graphene nanowalls (VGNWs) have emerged as a highly promising material in recent years due to their exceptional properties, such as a high specific surface area, excellent electrical conductivity, scalability, and compatibility with transition metal compounds. These attributes make VGNWs a compelling candidate for various applications, including energy storage, catalysis, and sensing, fostering great interest in their use in next future commercial graphene-based sensors like optoelectronic and plasmonic devices, energy storage electrodes, and catalytic systems. Among the diverse graphene synthesis methods, plasma-enhanced chemical vapor deposition (PECVD) has proven to be a robust technique for producing large-scale graphene films and creating VGNWs on diverse substrates. However, despite substantial progress in optimizing growth conditions to achieve micrometer-sized graphene nanowalls, the outcomes are often obtained through empirical approaches, and a comprehensive understanding of the underlying physicochemical mechanisms governing nanostructure formation remains elusive. In particular, a deeper exploration of atomic-level phenomena, such as nucleation, carbon precursor adsorption, and surface diffusion of adatoms, is imperative to exert precise control over the growth process. Concerning the synthesis of VGNWs, hydrogen plays a dual role in the graphene growth process, acting as both a co-catalyst and an etchant for the nanowalls. Nevertheless, a thorough comprehension of the intricate growth process is still required. To address these knowledge gaps, this review paper aims to investigate the nucleation and growth of VGNWs using PECVD, with a specific focus on exploring the temperature effect on the graphene growth ratio and nucleation density across a wide range of temperatures. By providing valuable insights into the PECVD process, our objective is to enable the optimization of growth conditions for tailoring VGNWs' properties, thereby facilitating their application in energy storage, catalysis, and sensing fields.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

The concept of “hyperferritinemic syndrome” defines a complex pathophysiological and clinical entity, characterized by a systemic hyperinflammatory state, generally associated with elevated levels of proinflammatory cytokines (hypercytokinemia) and high serum levels of ferritin (hyperferritinemia), traditionally recognized as an iron-binding plasma protein involved in the storage of iron in a biologically available form for different physiological cellular processes. Recent studies have shown that ferritin has other important functions as well, operating both as a proinflammatory mediator and as a immunosupressive agent, its elevated levels in the serum being detected in various conditions associated with inflammatory states, such as infectious diseases, autoimmune and autoinflammatory disorders and, in some cases, in malignancies. Catastrophic antiphospholipid syndrome (cAPS), systemic juvenile idiopathic arthritis (sJIA) and adult-onset Still’s disease (AOSD) and acquired forms of hemophagocytic lymphohistiocytosis (HLH), which includes macrophage activation syndrome (MAS), have been associated with hyperinflammatory states and dramatic elevations of serum ferritin, generating hyperferritinemic syndromes. Severe forms of coronavirus disease-2019 (COVID-19), in which MAS may frequently develop, has also been linked to the development of a hyperferritinemic syndrome. This review offers several insights into the physiological and pathophysiological roles of ferritin in several (hyper-)inflammatory diseases, but also into the causal entities, the underlying pathophysiological mechanisms, clinical manifestations and diagnostic features of somewhat obscure, yet potentially fatal pathological conditions, reunited under the concept of hyperferritinemic syndromes.

Projected future sea level rise and marine storminess is a serious threat for beaches as they induce beach flooding and erosion. Among other factors, wave runup play an important role in beach evolution and must be robustly assessed. However, little attention has been paid to the uncertainties associated to its characterization and how do they compare to other sources of uncertainty. As a first step towards this goal, we have quantified the impact of several sources of error in the estimation of wave runup on sandy beaches. Understanding what factors are more influential in the quality of the results will help to determine the main sources of uncertainty in beach flooding projections. To reach that goal, a calibrated state-of-the-art numerical modelling system has been setup for two beaches in the Mallorca islands (NW Mediterranean). The system has been forced with the best available information of nearshore incoming waves and has been validated against observations to define the benchmark quality. To determine the key factors affecting the quality of the system’s results, different systems configurations have been tested with different degrees of complexity.Our results show that using the most sophisticated modelling system with the best information on boundary conditions, bottom bathymetry, and submerged vegetation leads to a swash RMSE comparable to the standard deviation of the observed swash. We have also found that the choice of lateral boundary conditions (i.e., source of information for the incoming waves) can double the RMSE and induce large biases. Our results also show that using a simple empirical approach usually underestimates the wave runup. However, in locations with vegetated seabed there is a compensation error, and the empirical approach can lead to acceptable results if forced by nearshore waves. In addition, we have compared the error estimates obtained with uncertainties associated to projected sea level rise. Our findings suggest that the uncertainty associated with wave runup modelling should be considered in the assessment of the total uncertainty of future beach flooding, since the analysis performed indicates that this uncertainty can account for between 16% to 60% of the uncertainties linked to mean sea level projections.

This paper proposes a definition of fractional line integral, generalising the concept of fractional definite integral. The proposal replicates the properties of the classic definite integral, namely the fundamental theorem of integral calculus. It is based on the concept of fractional anti-derivative used to generalise the Barrow formula. To define the fractional line integrals the Gr\"unwald-Letnikov and Liouville directional derivatives are introduced and their properties described. The integral is defined first for broken line paths and afterwards to any regular curve

This paper presents a methodology based on deep learning models and metaheuristic algorithms for the optimization of airfoils for the design of aircraft wings with large endurance. The use of AZTLI-NN (a neural network with an architecture composed of a multilayer perceptron and a variational autoencoder) is implemented for the prediction of graphs of the aerodynamic coefficients of the airfoil as a function of the angle of attack. This neural network presents good predictions of the aerodynamic coefficients, similar to the coefficients obtained with computational fluid dynamics simulations. AZTLI-NN in combination of metaheuristic algorithms and the CST profile parameterization method show excellent performance in single-objective and multi-objective profile optimization tasks.

The potential of digital twin technology is yet to be fully realised due to its diversity and untapped potential. Digital twins enable systems’ analysis, design, optimisation, and evolution to be performed digitally or in conjunction with a cyber-physical approach to improve speed, accuracy, and efficiency over traditional engineering methods. Industry 4.0, factories of the future, and digital twins continue to benefit from the technology and provide enhanced efficiency within existing systems. Due to the lack of information and security standards associated with the transition to cyber digitisation, cybercriminals have been able to take advantage of the situation. Access to a digital twin of a product or service is equivalent to threatening the entire collection. There is a robust interaction between digital twins and artificial intelligence tools, which leads to strong interaction between these technologies, so it can be used to improve the cybersecurity of these digital platforms based on their integration with these technologies. This study aims to investigate the role of artificial intelligence in providing cybersecurity for digital twin versions of various industries, as well as the risks associated with these versions. In addition, this research serves as a road map for researchers and others interested in cybersecurity and digital security.

Abstract: Background: The periodization of physical exercise to optimize the objectives is common in competitive sports, however physical exercise programs for the older adults do not usu-ally present periodization in their programming, they are limited to carrying out similar sessions throughout the program. Methods:137 people over 60 years old performed a physical exercise program, 71 people participated in a multicomponent non-periodized program as the Control Group (CG) and 66 people participated in a program periodized in blocks as the Experimental Group (EG). The block periodization program was oriented to the development of strength, and was carried out in 86 sessions three times per week during a period of 8 months. Anthropometric assessments were made using: weight, height, BMI and electrical bioimpedance; and functional evaluations through standardized tests: SPPB, TUG, handgrip and two-minute stair test. Results: After the intervention, the EG presents significant improvements in the TUG, in the weight and in the BMI. On the other hand, the CG presents significant improvements in fat weight, in BMI and in the 2-minute stair test. The SPPB did not present changes after the intervention. Conclusion: The periodization of physical exercise for older adults does not have a significant impact on the functional capacity in this population group.

The ejido system in Mexico based on communal land was transformed for private ownership due to neoliberal trends during 1990. This research describes the evolution of Mexican land policies that changed the ejido system into private development to answer why land tenure change is shaping urban growth. To demonstrate this, municipalities of San Andrés Cholula and Ocoyucan were selected as a case study. Within this context, we evaluated how much ejido land is being urbanized due to real estate market forces and what type of urbanization model is created. These two areas represent different development scales: S.A. Cholula where its ejidos were expropriated as part of a regional urban development plan; and Ocoyucan where its ejidos and rural land were reached by private developers without local planning. To analyze both municipalities, historical satellite images from Google Earth were used with GRASS GIS 7.4 and corrected with QGIS 2.18. We found that privatization of ejidos fragmented and segregated the rural world for the construction of massive gated-communities. Therefore, a disturbing land tenure change occurred during the last 30 years, hence this research questions the role of local authorities in permitting land use change without regulations or local planning. The resulting urbanization model is a private sector development that isolates rural communities in their own territories, for which we provide recommendations.

This study introduces a sophisticated neural network structure for segmenting breast tumors. It achieves this by combining a pretrained Vision Transformer (ViT) model with a U-Net framework. The U-Net architecture, commonly employed for biomedical image segmentation, is further enhanced with Depthwise Separable Convolutional Blocks to decrease computational complexity and parameter count, resulting in better efficiency and less overfitting. The Vision Transformer, renowned for its robust feature extraction capabilities utilizing self-attention processes, efficiently captures the overall context within images, surpassing the performance of conventional convolutional networks. By using a pretrained ViT as the encoder in our U-Net model, we take advantage of its extensive feature representations acquired from extensive datasets, resulting in a major enhancement in the model’s ability to generalize and train efficiently. The suggested model has exceptional performance in segmenting breast cancers from medical images, highlighting the advantages of integrating transformer-based encoders with efficient U-Net topologies. This hybrid methodology emphasizes the capabilities of transformers in the field of medical image processing and establishes a new standard for accuracy and efficiency in activities related to tumor segmentation.

The duality is one of the most interesting properties of the Laplace and Fourier transforms associated to the integer order derivative. Here, we will generalize it for fractional derivatives and extend the results to the Mellin, Z and discrete-time Fourier transforms. The scale and nabla derivatives are used.

This article analyzes 6 probability distributions from the Generalized Pareto family, with 3, 4 and 5 parameters, with main purpose to identify other distributions from this family with applicability in flood frequency analysis compared to the distribution already used in the literature from this family such as Generalized Pareto Type II and Wakeby. This analysis is part of a larger and more complex research carried out in the Faculty of Hydrotechnics regarding the elaboration of a norm for flood frequency analysis using the linear moments method. In Romania, the standard method of parameter estimation is the method of ordinary moments, thus the transition from this method to the method of linear moments is desired. All the necessary elements for the distributions use are presented like, the probability density functions, the complementary cumulative distribution functions, the quantile functions, the exact and approximate relations for estimating parameters, for both methods of parameters estimation. All these elements are necessary for a proper transition between the two methods, especially since the use of the method of ordinary moments is done by choosing the skewness of the observed data depending on the origin of the maximum flows. A flood frequency analysis case study, using annual maximum and annual exceedance series, was carried out for the Prigor river, to numerically present the analyzed distributions. The performance of this distributions is evaluated using relative mean error, relative absolute error and linear moments diagram.

This article presents six probability distributions from the Gamma family with three parameters, for the flood frequency analysis in hydrology. The choice of the Gamma family of statistical dis-tributions was driven by its frequent use in hydrology. In the Faculty of Hydrotechnics, the im-provement of the estimation of maximum flows and including the methodological bases for the realization of a regionalization study with the linear moments method with the corrected pa-rameters was researched, being an element of novelty. The linear moments method is better than MOM because it avoids the choice of skewness depending on the origin of the flows, practiced in Romania. The L-moments method conforms to the current trend for estimating the parameters of statistical distributions. Observed data from hydrometric stations are of relatively short length, so the statistical parameters that characterize them are of a sample that requires correction. The correction of the statistical parameters is proposed, using the method of least squares based on the inverse functions of the statistical distributions expressed with the frequency factor for L-moments. All the necessary elements for their use are presented like, quantile functions, the exact and ap-proximate relations for estimating parameters and frequency factors. A flood frequency analysis case study was carried out for the Ialomita river, to verify the proposed methodology. The per-formance of this distributions is evaluated using Kiling-Gupta and Nash-Sutcliff coefficients.

Estimating the parameters of statistical distributions generally involves solving a system of nonlinear equations or a nonlinear equation, being a technical difficulty in their usual application in hydrology. This article presents improved approximations and, in some cases, new approximations for the estimation with the method of ordinary moments and the method of linear moments, which are useful for the direct calculation of the parameters, because the errors in the approximate estimation are similar to the use of iterative numerical methods. Thirteen statistical distributions of two and three parameters frequently used in hydrology are presented, for which parameter estimation was laborious. Thus, the approximate estimation of the parameters by the two methods is simple but also precise and easily applicable by hydrology researchers. The approximate forms characterized by very small errors are the result of the research conducted within the Faculty of Hydrotechnics to update the romanian normative standards in the hydrotechnical field.

The bilateral tempered fractional derivatives are introduced generalising previous works on the one-sided tempered fractional derivatives and the two-sided fractional derivatives. An analysis of the tempered Riesz potential is done and showed that it cannot be considered as a derivative.

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map on a pixel-by-pixel basis, the actual evapotranspiration (ET_a) of the Wonji Shoa Sugarcane Estate using the Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0 - 6.85, 0.0 – 9.36, 0.0 – 3.61, 0.0 – 6.83 mm/day; using SSEB 0.0 - 6.78, 0.0 – 7.81, 0.0 – 3.65, 0.0 – 6.46 mm/day, and SSEBop were 0.05 - 8.25, 0.0 – 8.82, 0.2 – 4.0, 0.0 – 7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ET_a over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop had higher ET_a values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season, ET_a is limited to water surplus areas only and in wet season, ET_a was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ET_a over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ET_a estimated for the whole estate were 107 Mm³, 140 Mm³, and 178 Mm³ using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate.

The decentralized treatment of wastes is studied for an urban scenario considering a high-density population of 2500 inhab./km2. Food and garden waste were assumed to be treated in a co-digestion configuration using several mid-size digesters. In contrast biogas and digestate valorization were carried out in a centralized manner. Electricity and thermal energy were produced from this configuration, accounting for 1.3% of residential electricity demand and 3.2% of thermal demand when using double-turbocharged engines. However, the location of the treatment plants is a factor that may raise social discomfort. Rejection of locating the plant in specific sites close to residential neighbors, nuisance due to possible odor and gaseous emissions, and house market distortions are just a few of a long list of problematic aspects that may threaten the decentralized alternative. These factors are of great relevance and must be given a practical solution if the circular economic model is to be implemented by considering the insertion of waste streams into the production system and generating local energy sources and raw materials.

In this paper we formally define the hierarchical clustering network problem (HCNP) as the problem to find a good hierarchical partition of a network. This new problem focuses on the dynamic process of the clustering rather than on the final picture of the clustering process. To address it, we introduce a new hierarchical clustering algorithm in networks, based on a new shortest path betweenness measure. To calculate it, the communication between each pair of nodes is weighed by the importance of the nodes that establish this communication. The weights or importance associated to each pair of nodes are calculated as the Shapley value of a game, named as the linear modularity game. This new measure, (the node-game shortest path betweenness measure), is used to obtain a hierarchical partition of the network by eliminating the link with the highest value. To evaluate the performance of our algorithm, we introduce several criteria that allow us to compare different dendrograms of a network from two point of view: modularity and homogeneity. Finally, we propose a faster algorithm based on a simplification of the node-game shortest path betweenness measure, whose order is quadratic on sparse networks. This fast version is competitive from a computational point of view with other hierarchical fast algorithms, and, in general, it provides better results.

Implementing the methodology of clinical simulation in the nursing degree course is a necessity in the European framework of higher education to acquire competences. The objectives of this research were to evaluate the strategies and techniques used during the simulations, identify the contents learned, and determine which of them are transferred to the nursing practice. We performed an observational, descriptive, and cross-sectional study from the nursing students’ perspective during the 2020-21-year course. On the one hand, our results show that the DASH scale helped us to obtain an internal validity of the simulations obtaining a mean score of 6.61 out of 7. On the other hand, the Ad Hoc scale, based on the competences were acquired in the simulations were transferred to the care practices. In conclusion, it is possible to improve care practices by integrating knowledge through clinical simulations.

This paper presents a novel approach to power management techniques in energy storage system (ESS) interoperability with the energy power system (EPS) by inserting a SCADA controlled directional protection relay for improving the mode switching sequence. According with latest European standards, all necessary measures for re-synchronization and reconnection for health work of the system must be taken. The proposed approach intends to improve the “interface” between storage systems and electric power grid by using a directional relay which provides interoperability improvement by automatic recognizing and differentiating the switching sequence of the mode of operation from the fault mode. Simulated results from a small scale electrical generating system are provided. The results demonstrate that the proposed power management solution is technically ideal to achieve high quality energy while retaining the stability of the power grid network. The interoperability of PHS systems integrated with the electric power grid usually leads to perturbations in terms of frequency of the generated voltage, and for improving it we designed an automatic treating and re-connecting software module. This work regards the importance of producing electricity from green and renewable energy sources, while retaining the stability and reliability of the power grid. ESS systems are widely used to help balancing of intermittent forms of load demand on the electrical power grid at specific key moments. In this article, the pumped hydro storage (PHS) technologies are proposed as an economical way to utilize smoothly the off-peak energy or surplus energy, by pumping water to a reservoir at a higher level. During peak load periods, the stored water is discharged through the reversible pump-turbine to generate electricity to meet the peak demand controlled by designed SCADA application.

Research rarely explores LGBTQ+ youth bullying in the context of culture-specific outcomes (e.g., LGBTQ+ identity development) and what can mitigate the impact of peer stressors. This study used a concurrent mixed methods design to explore how experiences of peer victimization predicted LGBTQ+ youth’s identity development (i.e., stigma sensitivity, concealment motivation, and difficult process) and whether social support and outness served as protective, moderating factors. The mixed-methods approach provides a culture-specific context via qualitative inquiry to inform whether the quantitative findings align with how youth qualitatively discuss their experience of bullying, negative outcomes, and social support. Our sample consisted of 349 LGBTQ+ youth 14-17 years old who completed a survey (quantitative sample), and a subset of 39 LGBTQ+ youth who completed a semi-structured interview (qualitative sample). Our quantitative findings indicated that greater overall peer victimization was positively related to LGBIS-revised subscales of stigma sensitivity, concealment motivation, and difficult process, where both outness and social support moderated such relations. Qualitatively, victimized youth also reported stigma sensitivity and concealment motivation, while also endorsing how being out and having a support system played a role in their experience of being victimized. These qualitative findings align with our quantitative findings that classmate support mitigated the effects of peer victimization on difficulty of coming out. Implications for practitioners and researchers are provided.

In response to the COVID-19 pandemic, and resultant cancellation of geoscience fieldwork, as well as outstanding accessibility issues inherent in conducting fieldwork, we developed a virtual geological fieldtrip (VFT) to the Huronian age deposits in the Whitefish Falls area, Ontario, Canada. This region is a geologically significant site in which many Ontario universities conduct undergraduate teaching due to the high-quality exposures. In this contribution we describe and comment on the development of this openly available resource, the motivations in doing so, the challenges faced, its pedagogical impact and relevance, as well as provide suggestions to others in the development of such resources. Our multimedia VFT combines 360° imagery, georeferenced data on integrated maps, and multi-scale imagery (aerial/drone, outcrop, and thin section images). The VFT was built using the Esri Storymaps platform, and thus offers us the opportunity to review the effectiveness of building such resources using this medium, as well as our approach to doing so. We conclude that the Esri Storymaps platform provides a sound medium for the dissemination of multimedia VFTs, but that some aspects of in-person fieldwork remain hard to replicate. Most notably, ‘hands on experience’ and specific activities such as geological mapping. In addition, while VFTs alleviate some accessibility barriers to geoscience fieldwork, substantial barriers remain that should remain the focus of both pedagogical and geoscience work.