Changes brought about by the Internet to Scholarly Communication and the spread of Open Access movement, have made it possible to increase the number of potential readers of published research dramatically. This two-phase study aims, at first, to assert the satisfaction of the potential for increased open access to articles published by authors at the University of Coimbra, in a context when there was no stimulus for the openness of published science other than an institutional mandate set by the University policy on Open Access (“Acesso Livre”). The satisfaction of the access openness was measured by observing the actual archiving behavior of researchers (either directly or through their agents). We started by selecting the top journal titles used to publish the STEM research of the University of Coimbra (2004-2013) by using Thomson Reuters’ Science Citation Index (SCI). These titles were available at the University libraries or through online subscriptions, some of them in open access (21%). By checking the journals' policy at the time regarding self-archiving at the SHERPA/RoMEO service, we found that the percentage of articles in Open Access (OA) could rise to 80% if deposited at Estudo Geral, the Institutional Repository of the University of Coimbra, as prescribed by the Open Access Policy of the University. As we concluded by verifying the deposit status of every single paper of researchers of the University that published in those journals, this potential was far from being fulfilled, despite the existence of the institutional mandate and favorable editorial conditions. We concluded, therefore, that an institutional mandate was not sufficient by itself to fully implement an open access policy and to close the gap between publication and access. The second phase of the study, to follow, will rescan the status of published papers in a context where the Portuguese public funding agency, the Fundação para a Ciência e a Tecnologia, introduced in 2014 a new significant stimulus for open access in science. The FCT Open Access Policy stipulates that publicly funded published research must be available as soon as possible in a repository of the Portuguese network of scientific repositories, RCAAP, which integrates the Estudo Geral.

In the framework of the FireStorm project, four portable weather stations were installed in the Lousã/Estrela mountain range. Given that the Portuguese Institute for Sea and Atmosphere’s sur-face network has two weather stations installed in this region, the new data allows an improved monitoring of the vertical variability of near-surface variables in this mountainous region. As most of the wildfires in mainland Portugal affect areas with complex terrain with elevations below 1200 m and major fires continue to burn overnight, it is also relevant to monitor the vertical changes of meteorological variables in the nighttime period, as these may exhibit large variability. This study provides the first assessment of the available data, with focus on the summer seasons of 2021 and 2022. The results highlight the large variability that was observed in the region and suggest that the risk of extreme fire behaviour in the nighttime period may be underestimated.

Cardiovascular diseases (CVDs) a leading cause of mortality worldwide. Therefore, there is in-creasing interest in dietary interventions to reduce risk factors associated with these conditions. Cherries and berries are rich sources of bioactive compounds and have attracted attention for their potential cardiovascular benefits. This review summarizes the current research on the effects of cherries and berries consumption on cardiovascular health, including in vivo studies and clinical trials. These red fruits are rich in phenolic compounds, such as anthocyanins and flavonoids, which have multiple bioactive properties. These properties include antioxidant, anti-inflammatory, and vasodilatory effects. Studies suggest that regular consumption of these fruits may reducing in-flammation and oxidative stress, leading to lower blood pressure, improved lipid profiles, and enhanced endothelial function. However, interpreting findings and establishing optimal dosages is challenge due to the variability in fruit composition, processing methods, and study design. Despite these limitations, the evidence highlights the potential of cherries and berries as components of preventive strategies against CVD. Further research is needed to maximize their health benefits and improve clinical practice.

The COVID-19 pandemic has contributed to mental health problems worldwide. Nurses are particularly prone to stress because they directly care for individuals with suspected or confirmed cases of COVID-19. The aim of this study is to explore the association between the mental health promotion strategies used by nurses during the coronavirus disease (COVID-19) outbreak and their symptoms of depression, anxiety, and stress, and to compare the strategies and symptoms of mental health nurses and non-mental health nurses. Cross-sectional study was conducted with a sample of 821 nurses. Portuguese nurses demonstrated high symptoms of depressive symptoms, stress, and anxiety. Healthy eating, physical activity, rest between shifts, maintaining social contacts, verbalizing feelings/emotions, and spending less time searching for information about COVID-19 are associated with better mental health. Mental health nurses have less depression, anxiety, and stress, and use more strategies to promote mental health than other nurses. We consider it important to promote nurses’ mental health literacy by encouraging them to develop skills and strategies aimed at improving their resilience and ability to deal with difficult situations while caring for the population.

Traditional population-based metaheuristic algorithms are effective in solving complex real-world problems but require careful strategy selection and parameter tuning. Parameter-less population-based optimization algorithms have gained importance due to their simplicity and efficiency. However, research on their applicability for solving large systems of nonlinear equations is still incipient. In this paper, a systematic review and detailed description of metaphor-less optimization algorithms is made, including the Jaya algorithm, the main Jaya variants for continuous optimization problems, with a focus on the Enhanced Jaya (EJAYA) algorithm, the three Rao algorithms, the best-worst-play (BWP) algorithm, and the very recent max-min-greedy-interaction (MaGI) algorithm. This paper also discusses a few previous parallelizations of the Jaya optimization algorithm, as well as recent GPU-based massively parallel implementations of the Jaya, Enhanced Jaya (EJAYA), Rao, and BWP algorithms developed by the authors. In addition, a novel GPU-accelerated version of the MaGI algorithm is proposed. The GPU-accelerated versions of the metaphor-less algorithms developed by the authors were implemented using the Julia programming language and tested primarily on GeForce RTX 3090 and NVIDIA A100 GPUs, as well as on Tesla V100S and Tesla T4 GPUs, using a set of difficult, large-scale nonlinear equation system problems. The computational experiments carried out produced quite significant speedups, which highlights the efficiency of the GPU-based versions of the metaphor-less algorithms developed for solving large-scale systems of nonlinear equations.

Cherries have been largely investigated due to their high content in phenolics in order to fully ex-plore their health-promoting properties. Therefore, this work aimed to assess, for the first time, the anti-inflammatory potential of phenolic-targeted fractions of Saco cherry, using RAW 264.7 mac-rophages stimulated with lipopolysaccharide. Additionally, the cytotoxic effects on gastric ade-nocarcinoma (AGS), neuroblastoma (SH-SY5Y) and normal human dermal fibroblast (NHDF) cells were evaluated, as well as the ability to protect these cellular models against induced oxidative stress. The obtained data revealed that cherry fractions can interfere with cellular nitric oxide (NO) levels by capturing NO radicals and decreasing inducible nitric oxide synthase and cyclooxygen-ase-2 expression. Furthermore, it was observed that all cherry fractions exhibited dose-dependent cytotoxicity against AGS cells, presenting cytotoxic selectivity for these cancer cells when compared to SH-SY5Y and NHDF cells. Regarding their capacity to protect cancer cells against oxidative injury, in most assays, the total cherry extract was the most effective. Overall, this study reinforces the sweet cherries incorporation in new pharmaceutical products, smart foods and nutraceuticals.

There is a need for alternatives or complements to synthetic fertilizers to enhance agricultural sustainability. Applying organic amendments can play a significant role in this. Insect droppings show high potential, though studies evaluating their agronomic value have only recently begun to emerge. This study compared black soldier fly (Hermetia illucens) and mealworm (Tenebrio molitor) larvae frass with another organic amendment (Nutrimais) derived from composting forestry, agro-industrial, and domestic waste. The experiment also included ammonium nitrate at two rates [the same as the organic amendments, 50 kg ha–1 nitrogen (N) (FullR), and half that rate (HalfR)] and an unfertilized control. The study spanned two growth cycles of lettuce (Lactuca sativa L.) grown in pots, followed by unfertilized oats (Avena sativa L.) to assess the residual effects of the fertilizing treatments. Mealworm larvae frass mineralized rapidly, with an apparent N recovery of 37.4% over the two lettuce growth cycles, indicating its high availability to soil heterotrophic microorganisms. The average dry matter yield (DMY) of lettuce was the highest among all treatments (12.8 and 9.8 g plant–1 in the first and second lettuce cycles), even compared to the FullR treatment (12.2 and 7.8 g plant–1), though without significant differences. Although mealworm larvae frass exhibited a high mineralization rate, the DMY cannot be attributed solely to N supply, as plants in the FullR treatment showed better N nutritional status. Mealworm larvae frass provided strong evidence of a plant biostimulant effect, not explained by the variables measured in this study. Black soldier fly larvae frass exhibited typical behavior of a moderately reactive organic amendment, while Nutrimais showed low reactivity, with a near-neutral mineralization/immobilization balance. The results suggest mealworm larvae frass is recommended for early maturing vegetable crops, whereas Nutrimais appears more suitable for perennial crops with low short-term nutrient requirements.

The “tubulin code” combines different α/β-tubulin isotypes with several post-translational modifications (PTMs) to generate microtubule diversity in cells. During cell division, specific microtubule populations in the mitotic spindle are differentially modified, but only recently has the functional significance of these modifications started to be elucidated. In particular, α-tubulin detyrosination of stable microtubules in the spindle was shown to guide chromosomes during congression to the metaphase plate and allow the discrimination of mitotic errors, whose correction is required to prevent chromosomal instability (CIN), a hallmark of human cancers. Although alterations in certain tubulin PTMs have been reported in human cancers, it remains unclear whether and how tubulin PTMs have any functional implications for cancer cell properties. Here we review the role of the tubulin code in chromosome segregation during mitosis, together with the emerging cancer tubulin code and discuss possible links, as well as the respective diagnostic, prognostic and therapeutic implications for human cancers.

Soil amendments with composted organic materials are recommended to increase soil organic matter (SOM), promote soil fertility, and the Circular Economy. Growing areas of hedged olive groves in southern Iberia peninsula generate huge amounts of olive leaves whose potential as soil organic amendment is not fully studied. An experimental field trial in a hedged olive grove (cv. “Cobrançosa”) was set up near Portalegre, Portugal, to test a compost of olive leaves plus sheep manure (2:1) applied in the row, at soil surface. Three nominal rates (0 or control, 2.5 and 5.0 kg m-2) were used, in a complete randomized block setup (3 treatments, 3 replicas, 9 plots) and soil chemical properties of layers 0-5, 5-15, and 15-30 cm deep were annually monitored. Results (mainly in layer 0-5 cm) showed increases in total N, carbon of the particulate organic matter (POM-C), permanganate oxidizable carbon (POX-C), extractable phosphorus, and zinc, after one year, and increases in soil organic carbon (SOC), C-stock, pHKCl, extractable phosphorus, and zinc, after two years. POX-C was the most sensitive SOM-related indicator, showing increases up to 30 cm deep after one year. This compost improved soil fertility, but should be monitored over longer periods of time, namely for SOC and extractable zinc content.

The COVID-19 pandemic crisis has brought about unprecedented economic and social consequences worldwide. The implementation of isolation measures, including national and international travel restrictions, significantly affected contact-intensive sectors such as tourism. During this lockdown period, Information and Communication Technology (ICT) was crucial in maintaining connectivity and enabling remote activities. Governments across the world implemented discretionary measures to mitigate the crisis's adverse effects on economic activity. This paper aims to analyze whether the level of ICT adoption and the importance of tourism influence the fiscal policy efforts pursued by governments. Based on the results of a linear regression analysis for 154 countries, the findings suggest that in countries with higher international tourism receipts, the governments had to promote higher fiscal stimulus. At the same time, ICT development diminished the efforts of the fiscal policy response to the crisis since it facilitated economic resilience. The findings of this study can contribute to understanding how governments responded to the pandemic crisis and the factors that influenced their fiscal policy decisions.

The global trade and transportation sectors heavily rely on the maritime industry. Still, its dependence on fossil energy sources poses significant environmental challenges and leads to unstable fuel prices that affect the cost of goods transported by sea. This paper aims to evaluate the viability of seaports as energy-intensive entities and explore the feasibility of implementing a Nuclear-Renewable Hybrid Energy System (NRHES). The study presents a case study of the Tanjung Priok Port in Indonesia, focusing on estimating energy consumption, emissions, and the potential impact of carbon taxation on seaport operations. By quantifying these factors, the research provides insights into the energy requirements, environmental effects, and potential costs associated with seaport carbon taxation. A comprehensive analysis of the technical and economic feasibility of implementing an NRHES in the seaport case study is conducted, determining the optimal sizing and composition of components, considering the proportion of nuclear and renewable energy sources. Additionally, the economic analysis considers energy costs, net present cost, cash flow, return on investment, and internal rate of return. The findings aim to inform decision-makers about the benefits and challenges of adopting an NRHES, contributing to a cleaner and more sustainable future for the maritime industry.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

Sphingolipids play an important role in the development of diabetes both type 1 and type 2 diabetes as well as in the development of both micro- and macro-vascular complications. Several reviews have been published concerning the role of sphingolipids in diabetes but most of the emphasis has been on the possible mechanisms by which sphingolipids, mainly ceramides, contribute to the development of diabetes. Research on circulating levels of the different classes of sphingolipids in serum and in lipoproteins and their importance as biomarkers to predict not only the development of diabetes but also of its complications has only recently emerged and it is still in its infancy. This review summarizes the previously published literature concerning sphingolipid-mediated mechanisms involved in the development of diabetes and its complications focusing on how circulating plasma sphingolipid levels and the relative content carried by the different lipoproteins may impact their role as possible biomarkers both in the development of diabetes and mainly in the development of diabetic complications. Further studies in this field may open new therapeutic avenues to prevent or arrest/reduce both the development of diabetes and progression of its complications.

The relationship between perception of anxiety and quality of life in caregivers of children with autism was verified. To verify quality of life, the Short Form Healthy Survey Item was used; perception of anxiety was assessed using the Beck Anxiety Inventory. 80 caregivers of children with autism participated, with 68.7% of caregivers being mothers. Of the total number of caregivers, 68.8% had a severe level of anxiety. Regarding quality of life, they demonstrated greater impairment in Limitation due to physical aspects, Limitation due to emotional aspects, Vitality and Pain. Caregivers with severe anxiety levels had worse quality of life in the domains of pain (p = 0.012), social aspects (p =< 0.001), limitation due to emotional aspects (p = 0.001) and mental health (p =< 0.001). However, in the functional capacity domain, caregivers with a moderate level of anxiety had a better physical capacity score (p = 0.001). There was a negative correlation between the general anxiety score and the general physical (p = 0.029) and general emotional component of quality of life (p =< 0.001). It was found that caregivers of children with ASD present losses related to psychological factors, quality of life and the lack of social support.

All types of sports are potential application scenarios for automatic and real-time visual object and event detection. In rink hockey, the popular roller quad skate variant of hockey team sports, it is of great interest to automatically track player’s movements and positions, player’s sticks and, also, making other judgments, such as being able to locate the ball. In this work, we introduce a real-time pipeline composed by an object detection model, created specifically for rink hockey games, followed by a knowledge-based event detection module. Even in the presence of occlusions and quick motions, our deep learning object detection model effectively identifies and tracks, in real-time, important visual elements such as: ball; players; sticks; referees; crowd; goalkeeper; and goal. Using a curated dataset composed by a collection of videos of rink hockey, comprising 2525 annotated frames, we trained and evaluated the algorithm performance and compare it to state of the art object detection techniques. Our object detection model, based on YOLOv7, presents a global accuracy of 80%, and presents a good performance in terms of accuracy and speed, according to our results, making it a good choice for rink hockey applications. In our initial tests, the event detection module successfully detected one important event type in rink hockey games, the occurrence of penalties.

This study aimed to conduct a cross-cultural adaptation of the development of the cat-owner/dog-owner relationship scales. The method encompassed several stages: conceptual, item, semantic, operational, measurement, and functional equivalence. Processes included translations, synthesis of translations, back-translations, consensus on the English versions, external evaluation by the original authors, expert committee evaluation, and pre-tests. The study involved surveying 342 pet owners throughout Brazil using a 20-item questionnaire. Data analyses utilized confirmatory factor analysis, covariance-based modeling, and multigroup analysis. The techniques confirmed that the scale preserved its psychometric properties and showed no variance between dog and cat owners, indicating that the measured constructs are universal and unaffected by specific cultural nuances. Hence, the cross-cultural adaptation and validation of the scale facilitate applying and testing concepts and measures in diverse contexts, enriching our understanding of the dynamics between owners and their pets (dogs and cats) in different living situations. In addition, this research holds particular significance in Brazil, given the country’s vast cultural diversity.

The main objective of this paper is to assess pro-environmental behavior, climate change perception, anxiety, hope and despair in different political orientations. Specific aims included to validate all the instruments; to assess whether the factor structure of the scales were valid across political orientations; to evaluate their reliability; to assess differences concerning age, gender and political orientation; to know the variables that explain pro-environment behavior; and to evaluate the moderating role of climate change perception, despair and hope in the relationship between climate change anxiety and pro-environmental behavior. Confirmatory factor analysis (CFAs), multi-group CFAs (to measurement invariance), multiple linear regressions and moderations were performed. Results showed that pro-environment behavior and climate change hope achieved the four levels of invariance across different political orientations; climate change anxiety achieved the three first levels of invariance; climate change perception and climate change despair achieved configural invariance. Climate change anxiety personal experience, climate change perception total, reality and consequences present higher values in left political orientation that in right or center. Climate change anxiety variables contribute most to explaining pro-environmental behaviors. Hope, despair and climate change perception consequences moderate de relationship between climate change anxiety and pro-environment behavior. These results open up new avenues of investigation, namely, to understand why high levels of anxiety lead to more pro-environment al behaviors.

Differences are introduced as outputs of linear systems called differencers, being considered two classes: shift and scale-invariant. Several types are presented, namely: nabla and delta, bilateral, tempered, bilinear, stretching, and shrinking. Both continuous and discrete-time are described. ARMA type systems based on differencers are introduced and exemplified. In passing, the incorrectness of the usual delta difference is shown.

This paper discusses the concept of fractional derivative with complex order from the application point of view. It is shown that a fractional derivative is hermitian, if and only if the order is real. The hermitian part of complex order derivatives behave like allpass filters with almost logarithmic phase.

A very high parking occupancy can negatively influence the traffic performance of an area by causing very long cruising times. A very low parking occupancy, on the other hand, is inefficient from a space utilization perspective. Thus, this paper proposes a framework to compute the optimal parking occupancy rate over a given time horizon based on a macroscopic traffic and parking model. This rate is set high enough to ensure an efficient usage of the parking infrastructure. However, it should also guarantee a high likelihood of finding parking in order to eliminate the drivers’ time wasted in cruising for parking and the added congestion it causes. The model outputs are based on small data collection efforts and low computational costs, and they can be generated without complex simulation software using a simple numerical solver. Multiple vehicle types are included into our methodology allowing us to generate insights about the optimal parking occupancy with or without differentiated parking (i.e., parking for specific vehicles, such as fuel and electric vehicles). In times of a modal shift towards electric vehicles, cities can use our model to evaluate how much parking supply (with battery charging opportunities) they would like to dedicate to electric vehicles in order to achieve optimal traffic and parking results, and whether a differentiated or semi-differentiated parking policy is desirable. We illustrate our framework in a case study of a central area within the city of Zurich, Switzerland, showing the traffic and parking impacts (e.g., average searching time for parking, total revenue created by parking fees, optimal parking occupancy rate) for different proportions of fuel and electric vehicles in the parking demand and/or supply. Our results confirm that optimal occupancy rates are between and for most realistic scenarios. We then discuss how these rates might change depending on various demand and supply relationships, and according to different parking policies. We show that equal proportions between electric vehicles in the demand and their parking spaces in the supply lead to the best traffic performance in the area. We also provide the tools for cities to analyze their loss in performance if they do not react, e.g., to an increasing demand for electric vehicles over time. Moreover, we illustrate how some of these risks can be mitigated by having more flexible parking policies, e.g., allowing electric vehicles to use parking spaces for fuel vehicles.

With the increment of the aging population in recent years, neurodegenerative diseases exert a major global disease burden, essentially as a result of the lack of treatments that can stop the disease progression. Alzheimer’s Disease (AD) is an example of a neurodegenerative disease, that affects millions of people globally, with no effective treatment. Natural compounds have emerged as a viable therapy to fill a huge gap in AD management, and in recent years, mostly fuelled by the Covid-19 pandemic, RNA-based therapeutics have become a hot topic in the treatment of several diseases. Treatments of neurodegenerative diseases face significant limitations due to the complex and interconnected pathways that lead to their hallmarks and, also due to the necessity to cross the blood–brain barrier. Nanotechnology has contributed to surpass this bottleneck in the treatment of AD, by promoting safe and enhanced drug delivery to the brain. In particular, exosome-like nanoparticles, a hybrid delivery system combining exosomes and liposomes' advantageous features, are demonstrating great potential in the treatment of central nervous system diseases.

The ceramic sherds from approximately 20 samples of lead-glazed tableware, recovered from diverse archaeological sites, including three repurposed storage pits transformed into dumpsters within the medieval city of Santarém (13th-14th century), underwent a meticulous examination. This investigation utilized techniques such as micro-Raman, ground state diffuse reflectance absorption, and X-ray fluorescence spectroscopies, in addition to X-ray diffraction and stereomicroscopy. A parallel study was conducted on contemporaneous European ceramics (glazed sherds) sourced from archaeological sites dating back to the 13th-15th centuries in Saintonge (France), Ardenne, Zomergem, and Bruges (Belgium), as well as Surrey-Hampshire, Kingston, and Cheam (England). The colour of the ceramic bodies is predominantly white or whitish, with a few exhibiting a vivid red hue. Ceramic sherds with a light paste composition were likely crafted using kaolin clays as raw materials. Analyses of fabric, mineralogical, and elemental composition of the sherds suggest that the majority of Santarém's glazed ceramics were locally or regionally produced, potentially derived from a Pliocene kaolin-rich sand formation. However, this conclusion is not supported by the absence of discovered lead glaze kilns or workshops in Santarém for the late Middle Ages. A distinctive feature from the European workshop ceramics lies in the quartz temper content and fabric.

Soil management in orchards can have several economic and environmental implications. In this study, three different soil management systems were compared in a dry-farmed olive grove: conventional tillage (Tillage), glyphosate-based herbicide (Herbicide) and Sheep Walking. The experiment lasted eleven years (2011-2022) and was carried out after a previous trial conducted on the same plot with the same treatments and duration (2001-2011). However, in the earlier trial, the Herbicide and Sheep Walking treatments switched positions in the plot, while the tillage treatment remained in its original place. The average total accumulated olive yields between 2011 and 2022 were 225.1, 230.9, and 245.0 kg tree–1 for the Sheep Walking, Tillage, and Herbicide treatments, respectively. However, no significant differences were observed between the treatments. The levels of total organic carbon in the soil, measured in samples collected in the last year of the study, were 41.3, 33.7, and 37.3 g kg–1, respectively for the same treatments. These findings indicated that the Tillage treatment exhibited lower soil organic matter content and reduced bioavailability of some nutrients, which raises concerns about its sustainability. On the contrary, employing Sheep Walking with an appropriate stocking rate, effectively controlling vegetation in the spring, ensured favourable soil properties and olive yields comparable to the other treatments. Moreover, the Sheep Walking approach provides supplementary advantages to the farmer, including revenue from the sale of animal products and the opportunity to transition to organic farming systems, which better align with the preferences of contemporary societies.

The relationship between religion and politics is a constant in the history of humanity. In the specific case of Western culture, it is possible to trace an archeology of the political as an effect of theological-political devices (essentially Christian-inspired). If we add to this the evolution of politics, in modern times, towards biopolitics, then the relationship focuses on very concrete topics. This is the case of the immunological process – from a personal, social, and philosophical perspective – thoroughly analyzed by Italian philosopher Roberto Esposito. In the context of his philosophical immunology, the place of religion is mainly archaeological and is interpreted critically. This article also aims to critically analyze his position, proposing a reading close to his thought but which is, at the same time, somewhat different.

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.

The transportation sector is a significant source of greenhouse gas emissions. Electric vehicles (EVs) have gained popularity as a solution to reduce emissions, but the high load of charging stations poses a challenge to the power grid. Nuclear-Renewable Hybrid Energy Systems (N-RHES) present a promising alternative to support fast charging stations, reduce grid dependency, and decrease emissions. However, the intermittent problem of renewable energy sources (RESs) limits their application, and the synergies among different technologies have not been fully exploited. This paper proposes a predictive and adaptive control strategy to optimize the energy management of N-RHES for fast charging stations, considering the integration of nuclear, photovoltaics, and wind turbine energy with a hydrogen storage fuel cell system. The proposed dynamic model of a fast-charging station predicts electricity consumption behavior during charging processes, generating probabilistic forecasting of electricity consumption time-series profiling. Key performance indicators and sensitivity analyses illustrate the practicability of the suggested system, which offers a comprehensive solution to provide reliable, sustainable, and low-emission energy to fast-charging stations while reducing emissions and dependency on the power grid.

The World Health Organization has defined the outbreak of the new coronavirus as a public health emergency of international concern. The average age of patients affected by the disease caused by the virus ranges from 49 to 59 years. The symptoms of coronavirus disease 2019 (COVID-19) infection include fever, cough, acute respiratory disease, and, in severe cases, the disease may progress to pneumonia and renal failure that may lead to death. Many oral and maxillofacial hospital procedures produce aerosol and droplets contaminated by blood, bacteria, and viruses. The purpose of this study is to gather recommendations from health authorities and scientific articles in order to educate surgeons regarding the procedures to assist and treat in oral and maxillofacial surgeries. The objective is to prevent the transmission of COVID-19 during the treatment of patients in urgent and emergency situations. The study’s methodology used the guidelines provided by the Brazilian College of Oral and Maxillofacial Surgery, in addition to the recommendations and epidemiologic data from national and international health authorities. The implementation of special precautions in oral and maxillofacial surgeries may elucidate questions related to the transmission of the disease by asymptomatic carriers and help control the spread of the virus.

In recent decades the Mediterranean area observed an increase in large fires, despite the decrease in the number of fire ignitions, following a worldwide tendency. Climate change has been the main culprit for large burnt areas, and alterations of forest ecosystems, resulting in the increased recurrence of forest fires. In Portugal, the analogous trend resulted in the destruction of large rural, urban and industrial areas, where after the 2017 months of June and October catastrophic events, the government implemented the 2019 specific policies for preventing fire outbreaks and defending the forest against fires. This compulsory policy demanded that landowners and local governments alike needed to contact specific authorities requesting authorization for their intentions to clean properties in and around urban areas, roads, and forest limits. Despite policy and careful monitoring, ignitions still occur, and in many cases resulting from the implementation of such policies. The study analyses the before and after policy implementation, considering 6904 ignitions records from the period between 2014 and 2023 from the central area of Portugal, covering the transition area between the agricultural fields of the Tagus valley and the Monte-junto-Estrela Mountain range, the district of Santarém. The authorization to use fire in clearance practices is granted according to a set of weather conditions, temperature, wind intensity, and relative humidity, when analyzing fire ignitions with the average daily wind intensity at the site of the occurrence, we observed that more than half of wildfires occur on days with winds between 10 and 20 Km/h, whereas intensities greater than 30 Km/h only 1% of the total occurrences, and of these 22% occurred due to the use of fire in the burning of agricultural leftovers and cut and piled bushes. The circulation of the thermal depression in the Iberian Peninsula gives rise to increasing intensity throughout the day, reaching a maximum in the late afternoon, this factor combined with the misjudgment of safe conditions leads us to suggest stricter intervals and the need for awareness of daily variation in conditions.

The search for graphene or few layer graphene production methods that are simple, allow mass production and yield good quality material continues to provoke intense investigation. The present work contributes through the study of the aqueous exfoliation of four types of graphene sources, namely graphite and graphite nanoflakes with different morphologies and geographical origin. The exfoliation was achieved in an aqueous solution of a soluble pyrene derivative that was synthesized to achieve maximum interaction with the graphene surface at low concentration (5 x 10-5 M). The yield of bilayer and few layer graphene obtained was quantified by Raman spectroscopic analysis and the adsorption of the pyrene derivative on the graphene surface was studied by thermogravimetric analysis and X-ray diffraction. The whole procedure was rationalized with the help of molecular modeling.

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.

The global pandemic of COVID-19 accounts for more than 14,000 deaths worldwide. However, little is known about the host genetics interaction with infection and COVID-19 progression. To better understand the role of host genetics, we review the current literature, aggregate readily available genetic resources, and provide some updated analysis relevant to COVID-19 and associated phenotypes. Using the unrelated individuals in UK Biobank (total n = 337,579 across 5 populations), we aggregate human leukocyte antigen and ABO blood type frequencies. We find significant and consistent risk reduction of blood group O reported in Zhao et al. and encourage broad sharing of ABO blood type frequencies that are readily accessible across COVID-19 with mild, moderate, and severe/critical symptoms for robust inferences at https://tinyurl.com/abo-covid19. In addition, we generate polygenic risk scores (PRSs) weights for 29 blood measurements, including clinically relevant haematological measurements for COVID-19, such as lymphocyte count and percentage. Focusing on the 8 most COVID-19 clinically relevant blood measurements, we performed PRS-PheWAS analysis across 44 disease antigen measurements (n = 6,643 unrelated individuals in White British group), infectious diseases and acute respiratory infections (n = 20,928 cases and 349,000 controls across 3 population groups) and deaths (n = 1,846 cases and 368,082 controls), recorded in hospital inpatient record and death registry data, respectively, in UK Biobank, and find host genetic PRS associations with disease risk. Taken together, we anticipate these resources (https://github.com/rivas-lab/covid19) will aid in improving our understanding of host genetic risk factors playing a role in SARS-CoV-2 infection and COVID-19 disease severity.

Currently, in a context of biorefinery and bioeconomy, lignocellulosic biomass is increasingly used to produce biofuels, biochemicals and value-added products. Microwaves and ultrasounds are emerging techniques that enable efficient and environmentally more sustainable routes in the transformation of lignocellulosic biomass. This review is divided into four parts. In Part I, the theoretical foundations of microwaves and ultrasounds are revisited. Dielectric constants for biomass, factors that influence pre-treatment, are some of the subjects addressed. In Part II, the effects that these technologies have on lignocellulosic biomass (on the size and surface area of the particle; on the content of lignin, hemicellulose and cellulose; on the crystallinity index of cellulose; on the effect of solubilization of organic matter; on hydrolysis and reduction of sugars) are analyzed. In Part III, emphasis is given on how microwaves and ultrasounds can contribute to the achievement of value-added products. In this context, several examples of liquefactions and extractions are presented. Part IV describes examples of sonocatalysis of lignocellulosic biomass to obtain value-added products such as for instancethe production of furfural, which is significantly reduced by ultrasound.

The World Health Organization estimates that every year air pollution kills seven million people worldwide. As it is expected that climate change will affect future air quality patterns, the full understanding of the links between air pollution and climate change, and how they affect human health, are challenges of future research. In this scope, a methodology to assess the air quality impacts on health was developed. The WRF-CAMx modelling framework was applied for the medium-term future climate (considering the SSP24.5 scenario) and for the recent past (considered as baseline). Following the WHO recommendations, mortality health indicators were used to estimate health impacts of long-term exposures. For that, the Aveiro Region, in Portugal, was considered as a case study. Future climate results indicate the occurrence of higher temperatures, and lower total precipitation. Despite that, improvements in the main pollutants’ concentrations, and consequently in the reduction of the related premature deaths are foreseen, mainly due to the reduction of pollutants emissions imposed by the European legislation for the upcoming years. The applied approach constitutes an added value in this research field, being crucial to anticipate the effects of climate change on air quality and evaluate their impacts on human health.

Natural polysaccharides, which are described in this study, are some of the most extensively used biopolymers in food, pharmaceutical and medical applications, because they are renewable and have a high level of biocompatibility and biodegradability. The fundamental understanding required to properly exploit polysaccharides potential in the biocomposite, nanoconjugate, and pharmaceutical industries is depended on detailed research of these molecules. Polysaccharides are preferred over other polymers because of their biocompatibility, bioactivity, homogeneity, and bioadhesive. Natural polysaccharides have also been discovered to have excellent rheological and biomucoadhesive properties, which may be used to design and create a variety of useful and cost-effective drug delivery systems. Polysaccharide-based composites derived from natural sources have been widely exploited due to their multifunctional properties, particularly in drug delivery systems and biomedical applications. These materials have achieved global attention and are in great demand because to their biochemical properties, which mimic both human and animal cells. Although synthetic polymers account for a substantial amount of organic chemistry, natural polymers play a vital role in a range of industries, including biomedical, pharmaceutical, and construction. As a consequence, the current study will provide information on natural polymers, their biological uses, food and pharmaceutical applications.Keywords: Polymers Biopolymers, Excipient, Natural source, Food and Pharmaceutical applications.

The fourth industrial revolution (4IR) can offer significant benefits to the construction sector, improving productivity, efficiency, collaborative efforts, and product quality while promoting safety and sustainability. However, research on the application of 4IR technologies in construction is scarce in developing countries. It is crucial to understand the ability of construction companies to adopt new technologies and identify factors influencing the success of technology implementation. In this study, a questionnaire-based survey was conducted with construction professionals to evaluate the level of technological development of the construction market in an emerging economy, assess the potential for innovation implementation, and identify factors that might influence technological development. Although respondents recognized the importance of digital transformation, the results showed that most innovations are in the early stages of implementation in the construction sector, particularly technologies that are essential for the consolidation of the 4IR. Understanding the factors underlying this reality can support the development of strategies to foster innovation and harness the advantages of the 4IR in the construction industry in developing countries.

Cancer is among the leading causes of death worldwide. Therefore, timely diagnosis and appropriate treatment are very important. There are many disadvantages that come with traditional cancer treatments, such as chemotherapy and radiotherapy. In these treatments, the specific drug concentration affects not only the tumor site but also healthy tissues or organs. One of the foremost promising uses of nanotechnology is in the field of medical technology and specific site targeting can be achieved due to manipulation of materials at a nanometric scale. Nanotechnology offers specific benefits in terms of cancer therapy by enhancing it and reducing its adverse effects by guiding drugs to selectively target cancer cells. In addition, the use of minute amounts of medicine can lead to cost savings. Furthermore, nanoparticles can also be used as imaging agents to improve cancer diagnostics, therapeutics, and treatment management. Thus, this review has focused on the different types of nanoparticles used in cancer therapy, their action mechanisms, and their benefits and applications in diagnosis, imaging, and treatment. This review sums up the parameters that need to be considered when designing systems for cancer therapy while considering the desired characteristics of the nanoparticles from the biological point of view.

The development of biofuels and biodiesel industry specifically, has resulted in the generation of large amounts of glycerol as a surplus. The conversion of glycerol, into chemicals with indus-trial interest, through anaerobic fermentation using E. coli as a biocatalyst is an attractive alter-native to improve economic performance in the biodiesel industry, for example through the bi-otransformation of residual glycerol into ethanol. For 2019, the size of the global ethanol market was valued at $ 89.1 billion US dollar. Biodiesel can be produced from several materials like rapeseed, palm, soya, corn, palm kernel, frying oil or olive-pomace oil (OPO). The last, can be extracted from alperujo, byproduct of olive oil process. However, olive-pomace oil converting into biodiesel is not enough established to achieve a global olive-oil/biodiesel derived process with minimized waste generation. Traditionally biodiesel production process produces an equivalent of 10% by mass of glycerol as a waste or by-product. This work explores the conver-sion of residual glycerol into chemicals like ethanol and hydrogen with a focus on projecting raw material potential availability from OPO, contributing to the promotion of the use of biofu-els and biodegradable compounds.

This study explores the dependence of drone acoustic detection systems performance on distance, using learning machines with different complexities, from simple linear discriminants, to deep neural networks, such as YAMNet, which exploits transfer learning. Other machine learning systems studied are the multilayer perceptron, support vector machines and random forest. These methods have been evaluated with a meticulously selected database that includes a wide variety of drone and interference sounds, previously processed by array signal processing and affected by ambient noise. Two strategies for training learning machines are considered. In the first one, they are trained with unattenuated signals, trying to preserve the information generated by the sound sources, but they are tested considering the attenuation with distance, achieving effective detection at distances up to 200 metres with some methods, especially linear discriminant. In all cases, the existence of interferences that hinder detection is considered. In the second strategy, the systems are trained and tested with attenuated signals as a function of distance. The effective detection range increases up to 300 metres for most methods and up to 500 metres for the YAMNet based detector. In addition, this second approach raises the possibility of developing specialised detectors for each distance range, thus significantly extending the effective detection range. These results underline the promising potential of acoustic detection of drones at various distances, encouraging further exploration in this research area.

The lymphocyte function–associated antigen-1 (LFA-1) (also CD11a/CD18 and αLβ2), is just one of many integrins in the human body, but its significance derives from its exclusive presence in leukocytes. In this review, we summarize the studies relating LFA-1 and its major ligand ICAM-1 (CD54) with cancer, through the function of lymphocytes and myeloid cells on tumor cells. We consider how LFA-1 mediates the interaction of leukocytes with tumors and the role of ICAM-1 in tumor dynamics, which can be independent of its interaction with LFA-1. A more detailed examination of LFA’s role within B-cell chronic lymphocytic leukemia is made. Finally, we discuss the role of LFA-1-harboring exosomes in tumor growth and metastasis.

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.

Extracellular vesicles (EV) are a very heterogeneous group of cell-derived vesicles released by almost all kind of living cells. EV are involved in intercellular communication, both locally and systemically, since they induce signals and transfer their contents (proteins, lipids, RNAs) to other cells, which subsequently trigger a wide variety of biological responses in the target cells. How-ever, cell surface receptor-induced EV release is limited to cells from the immune system, includ-ing T lymphocytes. T cell receptor activation of T lymphocytes induces secretion of EV containing T cell receptor for antigen and several bioactive molecules, including proapoptotic proteins. These EV are thus specific for antigen-bearing cells, which make them ideal candidates for a cell-free, EV-dependent cancer therapy. In this review we discuss the generation of EV by T lymphocytes and some potential therapeutic approaches of these EV.

Camelina (Camelina sativa L.) is an oilseed with potential for use as a raw material in second-generation biofuels. Camelina has a seed yield of up to 2380 kg ha^-1 and contains around 45% fatty acids. Selection of a suitable site is critical for production optimization. The objective of this study was to determine Chilean agro-climatic suitability for establishing camelina as a productive alternative. Climate and soil requirements and geographical restraints were evaluated for the species, considering the climatological characteristics of its regions of origin, as well as regions where camelina is successfully grown in the rest of the world. The variables considered include factors (maximum temperatures of the warmest month, water deficits, and degree days) and limitations (altitude, geomorphology, and current land use), which permitted the evaluation of the national territory for a certain level of suitability. It was determined that 1.3% of the national territory (960,664 ha) has some degree of suitability for camelina adoption. Between the Biobío and Los Lagos regions, 49.0% of land (471,203 ha) is in the category of without thermic restrictions, with mild water restrictions, and mild soil restrictions or without information, which can be used for camelina production. The Los Ríos region had 21.4% surface area (321,176 ha) with some level of suitability for camelina, the most suitable region to establish this crop in Chile.

Supply Chain Management (SCM) encompasses a wide variety of decision-making problems that affect business and supply chain performance as a whole. Since most of these problems involve uncertainty and hesitation on the part of Decision Makers (DMs), various studies have emerged recently that present SCM applications of techniques based on Hesitant Fuzzy Linguistic Term Sets (HFLTSs) and HFLTS extensions. Given the relevance of this subject and the lack of literature review studies, this study presents a systematic review of HFLTS and HFLTS extension applications to SCM decision-making problems. In order to answer a set of research questions, the selected papers have been classified in accordance with a group of factors that are pertinent to the origins of these studies, SCM, HFLTSs, and decision-making. The results demonstrate that the Source and Enable processes have been studied with greater frequency, while the most common problems have to do with supplier selection, failure evaluation, and performance evaluation. The companies of the automotive sector and Sustainable SCM and Green SCM strategies predominate in the analyzed studies. Even though most of the studies use techniques based on HFLTSs, we have identified applications of seven distinct HFLTS extensions, with Double Hierarchy Hesitant Fuzzy Linguistic Term Sets and Probabilistic Linguistic Term Sets being the most utilized. The identification of gaps in the literature presents avenues for future studies focused on innovative applications, integrations of techniques, comparisons of techniques, group decision-making, and validation procedures for new models. The results of this study offer a panorama of the state of the art in regard to this subject and can help researchers and practitioners develop new studies which involve the use of methods that employ HFLTSs and HFLTS extensions in SCM decision-making problems.

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.

Defining measures of network efficiency and vulnerability for networks is a pivotal aspect in modern networking paradigms. We approach this problem from a game-theoretical perspective. We will consider networks in which actors have social or economic interests modeled by means of a cooperative game. This allows to define, for each network, a family of efficiency measures and another of vulnerability measures, parameterized by the game. The proposed measures use the within groups and the between groups Myerson values. These two values respectively measure which part of the classical allocation of Myerson corresponds to the productivity of players and which part to the intermediation costs. Also, which part of total centrality in social networks is due to communication or to beteewnness. In our proposal, the efficiency of a network is the proportion of the total productivity (or centrality) that players can retain using the network topology. The intermediation costs (and the betweenness centrality) can be viewed as a weakness with a negative impact. Then, we propose to calculate vulnerability as the proportion expent by players in intermediation payments. We explore the properties of these measures and we particularize them to several structures and particular games, also analyzing their asymptotic behaviour.

The novel respiratory disease COVID-19 has reached the status of worldwide pandemic and large efforts are currently being undertaken in molecularly characterizing the virus causing it, SARS-CoV-2. The genomic variability of SARS-CoV-2 specimens scattered across the globe can underly geographically specific etiological effects. In the present study, we gather the 48,635 SARS-CoV-2 complete genomes currently available thanks to the collection endeavor of the GISAID consortium and thousands of contributing laboratories. We analyze and annotate all SARS-CoV-2 mutations compared with the reference Wuhan genome NC_045512.2, observing an average of 7.23 mutations per sample. Our analysis shows the prevalence of single nucleotide transitions as the major mutational type across the world. There exist at least three clades characterized by geographic and genomic specificity. In particular, the clade G, prevalent in Europe, carries a D614G mutation in the Spike protein, which is responsible for the initial interaction of the virus with the host human cell. Our analysis may drive local modulation of antiviral strategies based on the molecular specificities of this novel virus.

Since HIV was first identified, and in a relatively short period of time, AIDS has become one of the most devastating infectious diseases of the 21st century. Classical antiretroviral therapies were a major step forward in disease treatment options, significantly improving the survival rates of HIV-infected individuals. Even though these therapies have greatly improved HIV clinical outcomes, antiretrovirals (ARV) feature biopharmaceutic and pharmacokinetic problems such as poor aqueous solubility, short half-life and poor penetration into HIV reservoir sites, which contribute to the sub-optimal efficacy of these regimens. To overcome some of these issues, novel nanotechnology-based strategies for ARV delivery towards HIV viral reservoirs have been proposed. The current review focus on the benefits of using lipid-based nanocarriers for tuning the physicochemical properties of ARVs to overcome biological barriers upon administration. Furthermore, a correlation of these properties and the potential therapeutic outcomes has been established. Biotechnological advancements using lipid nanocarriers for RNA interference delivery for the treatment of HIV infections were also discussed.

Intrusion Detection Systems play a crucial role in a network. They can detect different network attacks and raise warnings on them. Machine learning-based IDSs are trained on datasets that, due to the context, are inherently large, since they can contain network traffic from different time periods and often include a large number of features. In this paper, we present two contributions: the study of the importance of feature selection when using an IDS dataset, while striking a balance between performance and the number of features; and the study of the feasibility of using a low-capacity device, the Nvidia Jetson Nano, to implement an IDS in a low-capacity network. The results, comparing the GA with other well-known techniques in feature selection and reduction, show that the GA has a higher F1-score of 76%, although the time to find the optimal set of features surpasses other methods; the reduction of the number of features reduces the processing time without a significant impact in f1-score. The Jetson Nano allows the classification of network traffic with an overhead of 10 times in comparison to a traditional server.

Digital transformation can become a complex process when workers have insufficient skills, which makes training in the digital field essential. Herein, we intended to relate digital literacy perceived by workers with their training needs for the Portuguese public sector context. Additionally, based in the Human capital theory, we also investigate which professional/demographic characteristics increase training propensity in digital fields. Through an online questionnaire, a dataset with information on 573 workers was obtained. Data analysis was made by using a probabilistic regression model and additional statistical techniques. The results revealed that workers with higher levels of education and higher professional skills have higher probability of participating in training in the digital field. On average, workers reveal low levels of digital knowledge and low participation in training in the digital fields, but the majority present a willingness to participate in future training sessions, especially in the fields of Dataset management, Cybersecurity and Communication systems. This study provides information on training in the digital field of workers in the public sector, which is essential for public organizations to better prepare for digital transformation. Additionally, it contributes to a very recent literature on digital learning, and it can be extended to other contexts.

This work mainly aims to identify and understand the factors influencing the switching of transportation modes among higher-education students in Joinville, Brazil when traveling to universities. Furthermore, this study evaluates the possibility of switching from individual vehicles to other modes of transport (i.e., bus, bicycle, and walking) by employing a multinomial logit model. The results indicate that students would be interested in switching from individual motor vehicles to other options. The scenarios for switching to buses presented the highest switching probability. The bus cost was the most important factor for switching. Meanwhile, the parking space reduction does not affect the student's choice, indicating that restricting available spaces should not be an isolated measure for decreasing the car mode attractiveness. Finally, the transport mode switch would occur only if alternative modes to the car or their infrastructure are improved; otherwise, students maintain their usual choices.

This paper reviews the unilateral and bilateral, one- and two-dimensional Laplace transforms. The unilateral and bilateral Laplace transforms are compared in the one-dimensional case, leading to the formulation of the initial-condition theorem. This problem is solved with all generality in the one- and two-dimensional cases with the bilateral Laplace transform. General two-dimensional linear systems are introduced and the corresponding transfer function defined.

Retailers must have accurate sales forecasts to operate their businesses efficiently and effectively and to remain competitive in the marketplace. Global forecasting models like RNNs can be a powerful tool for forecasting in retail settings, where multiple time series are often interrelated and influenced by a variety of external factors. By including covariates in a forecasting model, we can better capture the various factors that can influence sales in a retail setting. This can help improve the accuracy of our forecasts and enable better decision-making for inventory management, purchasing, and other operational decisions. In this study we investigate how the accuracy of global forecasting models is affected by the inclusion of different potential demand covariates. To ensure the significance of the study's findings, we used the M5 forecasting competition's openly accessible and well-established dataset. The results obtained from the DeepAR models, which were trained on various combinations of features including time, price, events, and IDs, suggest that individually only the features corresponding to IDs improve the baseline model. However, when all the features are used together, the best performance is achieved, indicating that the individual relevance of each feature is emphasized when the information is given jointly. Comparing the model with features to the model without features, there is an improvement of 1.76\% for MRMSSE and 6.47\% for MMASE.

The main objective of this investigation was to study the effect of organizational competencies development practices on turnover intentions and whether affective commitment explains this relationship. Another of the study's objectives was to test whether these relationships vary ac-cording to the generation to which the participant belongs. The study sample consisted of 2123 participants working in Portuguese organizations. The results indicate that organizational com-petencies development practices (training, individualized support, and functional rotation) nega-tively and significantly affect turnover intentions and that affective commitment mediates this re-lationship. However, these relationships vary according to the participant's generation. For Gen-eration Y and Generation X, this mediating effect is found in all dimensions of organizational competencies development practices. For the baby boomer generation, there is only a mediating effect of affective commitment in the relationship between individualized support and turnover intentions. These results indicate that human resources should consider the generation to which the participant belongs when implementing competencies development practices.

In this paper is presented the design and syntheis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasable representation for this kind of robot. Then two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control, this means, that considering that the velocity vector of the mobile robot is orthogonal to its restriction a dynamic output feedback and neural network controller is designed in order that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then another control strategy is designed for trajectory tracking purposes, which similar to the driftless controller, a kinematic control scheme is provided but suitable to implement in more sophisticated hardware. In both control strategy a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory the stability and convergence to the origin of the mobile robot position coordinates is ensured. Finally, two numerical experiment are presented in order to validate the theoretical results synthetized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.

Angiotensin-converting enzyme 2 (ACE2) is an important player of the renin-angiotensin-aldosterone system (RAAS) in regulating the conversion of angiotensin II into angiotensin (1-7). While expressed on the surface of human cells, such as lung, heart, kidney, neurons, and endothelial cells (EC), ACE2 is the entry receptor for SARS-CoV-2. Here, we would like to highlight that ACE2 is predominant on the EC membrane. Many of coronavirus disease 2019 (COVID-19) symptoms have been associated with the large recruitment of immune cells, directly affecting EC. Additionally, cytokines, hypoxia, and complement activation can trigger the activation of EC leading to the coagulation cascade. The EC dysfunction plus the inflammation due to SARS-CoV-2 infection may lead to abnormal coagulation, actively participating in thrombo-inflammatory processes resulting in vasculopathy and indicating poor prognosis in patients with COVID-19. Considering the intrinsic relationship between EC and the pathophysiology of SARS-CoV-2, EC-associated therapies such as anticoagulants, fibrinolytic drugs, immunomodulators, and molecular therapies have been proposed. In this review, we will discuss the role of EC in the lung inflammation and edema, in the disseminate coagulation process, ACE2 positive cancer patients, and current and future EC-associated therapies to treat COVID-19.

Acne vulgaris is a prevalent dermatological disorder that impacts the quality of life for millions of people around the world. The multifactorial nature of this disorder requires innovative and effective treatment strategies. Over time, there has been a growing interest regarding the use of natural topical therapies, with cannabinoids emerging as a promising group of compounds for investiga-tion. In the context of acne treatment, cannabinoids are of particular interest due to their anti-acne properties, namely, lipostatic, anti-inflammatory, antiproliferative, and antimicrobial activities. Among these bioactive compounds, cannabidiol stands out as a notable derivative, exhibiting a promising spectrum of therapeutic actions. Pre-clinical and clinical studies have proven its ability to modulate sebum production, reduce inflammation, and inhibit bacterial proliferation - all of which are critical components in the pathogenesis of this dermatosis. This review provides a comprehen-sive overview of cannabinoids' potential as a novel and holistic approach to acne vulgaris treatment and summarizes recent developments in this area.

The aim of this study was to analyze the level of specific back-health-related physical activity and exercise knowledge. This is a cross-sectional study. A representative sample of 1500 students were recruited with a confidence level of 95% and an accepted standard error of ±2.53%. Individuals were aged between 13 and 18 years old (mean age= 15.18; SD = ±1.446). Self-reported questionnaires were used to record back-health-related physical activity and exercise knowledge concerning back care in adolescents. The level of specific knowledge of back health education related to physical activity and exercise in adolescents was low (X = 2.05, SD = ±2.264). Only 10.9% of the students passed the specific knowledge test, achieving a grade equal or superior to 5. The boys average score was higher (X = 2.17, SD = ±2.312) than the girls (X = 1.94, SD = ±2.212) with statistically significant differences (p = .048). The level of specific knowledge increased with age (F = 11.531; p &lt; .001). High school students have a low level of specific knowledge. Physical Education teachers should apply the conceptual content properly. Knowledge is the first step towards changing behavioral habits. Back care education in the school curriculum is recommended.

A cross-sectional study was conducted to gain insight into the epidemiology of canine ehrlichiosis and rickettsiosis in northern Portugal. Specific IgG antibodies to Ehrlichia canis were analysed using a commercial indirect ELISA test, and antibodies to Rickettsia conorii using a commercial IFAT. A total of 113 dogs from two different shelters were sampled, and seroprevalence values of 0.9% (95% confidence [CI]: 0.2–4.8%) for E. canis and 9.7 (95% CI: 5.5–16.6%) for R. conorii were found. Univariable models investigated risk factors for seropositivity. The odds ratios (OR) of R. conorii seropositivity were higher for female dogs (OR = 2.32; 95% CI: 1.58–3.39) and for dogs belonging to Shelter 2 (OR = 3.0; 95% CI: 2.28–3.95). Seropositive dogs for co-infection (E. canis + R. conorii) were more frequently observed in females (OR = 2.4; CI 95%: 1.66–3.47) and in Shelter 2 (OR = 2.72; 95% CI: 1.97–3.76). These findings show that shelter dogs in northern Portugal are exposed to E. canis and R. conorii, which can affect both canines and humans. It is imperative to adopt a One Health approach to educate the public about the hazards of canine zoonoses and develop legislation and procedures to control their spread and preserve public health.

Copper-nitride (Cu3N) semiconductor material is attracting much attention as a potential, next-generation thin-film solar-light absorber in solar cells. In this communication, polycrystalline Cu3N thin films were prepared using reactive-RF-magnetron-sputtering deposition, at room temperature, onto glass and silicon substrates. The very-broadband optical properties of the Cu3N thin film layers were studied by UV-MIR (0.2-40 μm) ellipsometry and optical transmission, to be able to achieve the goal of a low-cost absorber material to replace the conventional silicon. The reactive-RF-sputtered Cu3N films were also investigated by focused ion beam scanning electron microscopy, and both FTIR and Raman spectroscopies.

In recent decades, the requirements for implantable medical devices increased, but the risks of implant rejection still exist. These issues are primarily associated with poor osseointegration, leading to biofilm formation on the implant surface. This study focuses on addressing these issues by developing a biomaterial for implant coatings. 45S5 Bioglass has been widely used in tissue engineering due to its ability to form a hydroxyapatite layer, ensuring a strong bond between the hard tissue and the bioglass. In this context, 45S5 bioglasses, modified by the incorporation of different amounts of copper oxide, from 0 to 8 mol%, were synthesized by the melt-quenching technique. The incorporation of Cu ions does not show a significant change in the glass structure. Since the bioglass exhibited the capacity of being polarized, and therefore promoting the osseointegration effectiveness, the electrical properties of the prepared samples were studied using the impedance spectroscopy method, in the frequency range of 102-106 Hz and temperature range of 200-400 K. The effects of CuO on charge transport mobility were investigated. Additionally, the bioactivity of the modified bioglasses was evaluated through immersion tests in simulated body fluid. The results revealed the initiation of a Ca-P-rich layer formation on the surface within 24 h, indicating the potential of the bioglasses to enhance the bone regeneration process.

Several clinically useful anticancer drugs selectively kill cancer cells by inducing DNA damage; the genomic instability and DNA repair defects of cancer cells make them more vulnerable than normal cells to the cytotoxicity of DNA-damaging agents. Because epoxide-containing compounds can induce DNA damage, we have used the MTT assay to evaluate the selective cytotoxicity of three epoxyalkyl galactopyranosides against A549 lung cancer cells and MRC-5 lung normal cells. Compound (2S,3S)-2,3-Epoxydecyl 4,6-O-(S)-benzylidene-β-D-galactopyranoside (EDBGP) showed the highest selective anticancer activity and was selected for mechanistic studies. After observing that EDBGP induced cellular DNA damage (comet assay), we found that cells deficient in nucleotide excision repair were hypersensitive to the cytotoxicity of this compound; this suggests that EDBGP may induce bulky DNA adducts. EDBGP did not inhibit glycolysis (glucose consumption and lactate production). Pre-treatment of lung cancer cells with several antioxidants did not reduce the cytotoxicity of EDBGP, thereby indicating that reactive oxygen species do not participate in the anticancer activity of this compound. Finally, EDBGP was screened against a panel of cancer cells and normal cells from several tissues, including three genetically modified skin fibroblasts with increasing degree of malignancy. Our results suggest that epoxyalkyl galactopyranosides are promising lead compounds for the development of new anticancer agents.

Computer extended Descriptive Geometry (CeDG) is a new approach to solve and build computer models of three dimensional (3D) geometrical systems through descriptive geometry procedures that have demonstrated reliability and accuracy. CeDG may calculate a parametric algebraic exact form for the spatial curves generated in the intersection of two surfaces, as well as of the flattened pattern of any developable surface involved in those encounters. This study presents first the theoretical foundations and methodology to calculate those parametric algebraic curves. Secondly, a compound hopper is defined and modelled through CeDG (implemented in GeoGebra) and CAD (Solid Edge 2023) approaches to evaluate the advantages of CeDG against CAD. The results demonstrate the robustness and accuracy of the CeDG technique for surfaces intersection and flattening and the advantages of CeDG against Solid Edge 2023 in solving the hopper case study.

With the continuous growth of electric and electronic appliances’ usage, the waste produced with obsolete material (e-waste) has an increasing environmental impact. Also, the production of such appliances bears to increased consumption of natural resources and produces a multitude of toxic and hazardous substances, which typically are not properly treated. One of the approaches that may be adopted to reduce such problems relies on the circularization of the current linear model, commonly adopted in the EEE value chain. This includes recovering eol products and reintroducing its parts, components, or raw materials into the value chain (e.g. semiconductors, circuit boards, raw metals, etc.), thus contributing to a more sustainable value chain. In this article, we present a state-of-art review that focuses on approaches and solutions for the EEE value chain traceability, and analyses the technologies that may be beneficial for promoting and implementing the CE model in this value chain.

A Digital marketing allows brands to disseminate information in a targeted way towards their clients and consumers, making bidirectional communication and interactions between organizations and audiences feasible. This reality not only allows companies to pass on messages about sustainability associated with processes and products with the aim of launching trends and shaping behaviour, but also allows consumers to share their experiences, needs, preferences and expectations. In this sense, the techniques used in the context of digital marketing make it possible not only to communicate products and services but also to show that brands are working to be more sustainable and to disseminate new sustainable trends that help to change consumer mindsets. This research paper employs a Systematic Literature Review with Bibliometric Analysis (SLBA) methodology to explore and synthesize data about how digital marketing can be used to promote and communicate sustainability. In this study, the results show that digital marketing strategies contribute to promoting sustainable development by encouraging sustainable consumption patterns. This scenario is possible by understanding consumer behavior, communicating key messages through the best channels and effectively evaluating green marketing campaigns on consumer attitudes and purchasing decisions.

In the present study, a numerical model was developed to predict the flow pattern inside a broiler building. The model intends to predict the velocities fields inside the domain and ammonia (NH3) emitted or released by litter from poultry housing. The numerical model developed in Computational Fluid Dynamics (CFD) commercial code, intends to represent a commercial broiler building, and intends to simulate the 3D and heat transfer, in steady state flow. The evaporative cooling pads were also included in the model. The validation of the model was based in experimental measurements obtained in previous studies. The simulations were focused on Summer, Winter and also Mid-Season situation. The numerical results of NH3 concentration were compared with the experimental measurements, and a quite good agreement was verified. The numerical results allowed the characterization of: the inside flow pattern developed for the summer and winter situation; the inside NH3 distribution, and the velocity field distribution inside the broiler building. It was found that NH3 concentration increases along the tunnel, especially in low flow rate imposed from the exhaust fan. Also, it was verified that the low velocities inside domain are no sufficient to remove the gaseous pollutants.

In no-tillage systems, there is an accumulation of crop residues (CR) which plays an important role in available of soil-N. A study was set up to provide information regarding the CR N credit, and the influence of N mineral fertilizer. An incubation was run in a loam soil with addition of a similar rate of residue (10 Mg ha-1; sugarcane, soybean, and brachiaria) and N mineral fertilizer (urea; 120 kg N ha-1). After the stabilization of biological activity, soil and remaining residues were collected, and N monitored. Results showed that the N credit was positive with application of soybean, sugarcane, and brachiaria. There was an expressive performance of soybean N credit represented by a positive balance, and a reduction from 2.49 to 0.9 g kg-1 of N in residue, with direct increase of 90% of soil-N. There is no need of N fertilizer to potentialize the soybean N credit, but it is requested to potentialize N credit of brachiaria and sugarcane. The urea demonstrated be a good enhancer of brachiaria N credit, but it was not adequate to sugarcane residues. Based in our result, the accumulation and incorporation of CR can be considered as a N credit with positive contribution in soil-N.

This paper aims to demonstrate that, beyond the small world of Riemann-Liouville and Caputo derivatives, there is a vast and rich world with many derivatives suitable for specific problems and various theoretical frameworks to develop, corresponding to the different paths taken. Notions of time and scale sequences are introduced and general associated basic derivatives, namely right/stretching and left/shrinking, are defined. A general framework for fractional derivative definitions is reviewed and applied to get both known and new fractional order derivatives. Several fractional derivatives are considered, mainly: Liouville, Hadamard, Euler, bilinear, tempered, q-derivative, and Hahn.

A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements in a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling by resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridization. An induction motor controller which must be able to maintain a constant air flow through a filter is one of these systems and it is discussed in the paper as a study case of closed-loop control system. The article discusses a practical application of ML methods that demonstrates how to replace such closed loop in industrial control systems with a Simulink block generated from neural networks to show how the proposed procedure can be applied to derive complete hybrid system designs with artificial neural networks (ANN). In the proposed ANN-based method to design a real-time hybrid system with continuous and discrete components, we use a typical design of a neural network, in which we define the usual phases: training, validation, and testing. The generated output of the model is made up of reference variables values of the cyber-physical system, which represent the functional and dynamic aspects of model. They are used to feed Simulink/Stateflow blocks in the real target system.

Elliptic scator algebra is possible in 1+n dimensions, n∈N. It is isomorphic to complex algebra in 1+1 dimensions, when the real part and any one hypercomplex component are considered. It is endowed with two representations: an additive one, where the scator components are represented as a sum; and a polar representation, where the scator components are represented as products of exponentials. Within the scator framework, De Moivre’s formula is generalized to 1+n dimensions in the so called victoria equation. This novel formula is then used to obtain compact expressions for the integer powers of scator elements. A scator in S1+n can be factored into a product of n scators that are geometrically represented as its projections onto n two dimensional planes. A geometric interpretation of scator multiplication in terms of rotations with respect to the scalar axis is expounded. The powers of scators, when the ratio of their director components is a rational number, lie on closed curves. For 1+2 dimensional scators, twisted curves in a three dimensional space are obtained. Collecting previous results, it is possible to evaluate the exponential of a scator element in 1+2 dimensions.

A robust methodology to simulate virtually the residual stresses pattern in welded steel plates is presented. The methodology is applied to the structural analysis of typical welded plates belonging to ship structures, and the effect of residual stresses on the elastoplastic behavior of plates loaded axially is analyzed in comparison to the residual stress free case, both for tension and compression and including initial imperfections. Residual stresses affect in different manner plates with different geometries; thus a parametric study is performed covering the usual range of variation of the most important plate parameters that control the strength of the plates, more precisely the slenderness and the aspect ratio. The results from finite elements analysis are compared with codes and most stablished formulations and recommendations of applicability in the prediction of load-shortening curves for hull’s bending strength evaluation, ultimate strength and ultimate strain of plate elements are made.

In this brief paper a quantum algorithm to calculate the Hamming distance of two binary strings of equal length (or messages in theory information) is presented. The algorithm calculates the Hamming weight of two binary strings in one query of an oracle. To calculate the hamming distance of these two strings we only have to calculate the Hamming weight of the xor operation of both strings. To test the algorithms the quantum computer prototype that IBM has given open access to on the cloud has been used to test the results.

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020-2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment's effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.

This article explores the synergies and progression of feminism towards a comprehensive, emancipatory and sustainable policy from a theoretical point of view, particularly from a radical gender focus, suggesting the masculinist theory as a complement in the fight against the patriarchal-capitalist system, whose greatest achievement was to use a ‘feminist rhetoric’ with no feminist content, which implies a hidden reconfiguration, even more patriarchal, of the geographical borders of countries from the notion of State-nations to the entrepreneurial-nations. A theoretical model is proposed to analyse the adoption and compliance feminist behaviour in order to identify the uncompliant and unsustainable behaviour, that is, the friendly machismo or feminism light. Finally, in a preliminary manner, the foundations of a new masculinist theory and policy will be listed as a necessary step towards a deeply feminist and radical emancipatory policy.

This article analyses from a post-Marxist view, particularly, an ecological and gender-oriented perspective, the perception and attitudes of the Mexican people by gender, political affiliation and income level towards such current environmental issues as global warming, water shortage, water pollution and the influence of economic growth on the environment, among others. It highlights the influence of political ideology on the environment and of gender awareness on conservation and a more positive attitude towards ecological issues, despite women having usually been excluded from the administrative and decision-making arenas. A new theoretical model is proposed related to the Responsibility Footprints, a new concept more critical than the neoliberal Corporate Social Responsibility. The data for this study come from the 2012 International Social Survey Program. The results analysed brought to light some relevant questions for designing public policies that will greatly bolster initiatives to prompt better female professional involvement in the conservation of natural resources.

(1) Background: The purpose of this study was to investigate the relationship between IMO and burnout while assessing the contribution of job demands and resources on increasing internal orientation and worker well-being and, consequently, the levels of perceived performance; (2) Methods: Data were collected between April and December 2021 by completing an online questionnaire, developed in the Google Forms platform. The following descriptive statistics were analyzed: measures of central tendency (mean), dispersion (standard deviation), minimum value and maximum value. Next, Pearson's correlation coefficient was calculated to analyze the relationship between the variables under study.; (3) Results: The results showed the mediating effect of IMO between performance feedback and perceived performance, while burnout mediates the relationship between emotional and technology demands and perceived performance. (4) Conclusions: These conclusions demonstrate that constructive feedback might help a more efficient performance through better internal communication and the positive effects of technology demands could be the result of the interaction between personal and organizational resources.

Oral mucositis is most frequently a toxic effect of chemotherapeutic and/or radiotherapeutic treatment, resulting from complex multifaceted biological events involving DNA damage. The clinical manifestations have a negative impact on the life quality of cancer patients. Preventive measures and curative treatment of mucositis are still not well established. The glycine has anti-inflammatory, immunomodulatory and cytoprotective actions, being a potential therapeutic in mucositis. The objective was to evaluate the effects of glycine on the expression of collagen and growth factors, platelet and epidermal in oral mucositis. The mucositis of which was induced by the protocol of Sonis. 40 hamsters were used, divided into two groups: Group I- control; Group II- supplemented with 5% intraperitoneal glycine, 2,0 mg/g diluted in hepes. Histopathological sections were used to perform the immune-histochemical method, the evaluation collagen expression and the growth factors: EGF and PDGF. It was observed that the group supplemented with glycine higher amounts of collagen expression and predominance type of collagen I. The glycine group presented lower immunoexpression of the growth factors, EGF and PDGF. The group supplemented with glycine showed a marked healing process of the oral mucosite, demonstrated by the predominance of collagen type I and reduction of growth factors, EGF and PDGF.

Polyalcohol liquefaction can be done by acid or basic catalysis producing polyols with different properties. This study compared the mechanical properties of foams produced using polyols from liquefied Cytisus scoparius obtained by acid and basic catalysis and using two different foam catalysts. The differences were monitored using FTIR analysis. Acid-catalyzed liquefaction yielded 95.1 %, with the resultant polyol having an OH index of 1081 mg KOH/g while basic catalysis yielded 82.5 %, with a similar OH index of 1070 mg KOH/g. Generally, compressive strength with dibutyltin dilaurate (DBTDL) ranged from 16 - 31 kPa (acid-liquefied polyol) and 12 -21 kPa (base-liquefied polyol), while with stannous octoate (TIN), it ranged from 17 - 42 kPa (acid) and 29 - 68 kPa (base). Increasing water content generally decreased the compressive modulus and strength of foams. Higher water content led to a higher absorption at 1670 cm-1 in the FTIR spectrum due to the formation of urea. Higher isocyanate indices generally improved compressive strength, but high amounts led to unreacted isocyanate that could be seen by a higher absorption at 2265 cm-1 and 3290 cm-1. DBTL was shown to be the best foam catalyst due to higher trimer conversion seen in the spectra by a higher absorption at 1410 cm-1. Acid and base-derived polyols lead to different polyurethane foams with different FTIR spectra, particularly with a higher absorption at 1670 cm-1 for foams from acid-derived liquefaction.

Background: The presence of a leadership role in the nursing manager appears to be closely related to a positive and productive work environment within health settings. In some contexts, such as Mexico, the profile of the nursing manager has not been formally defined, and, sometimes those who occupy these positions do not always have sufficient training, and therefore this vocation, which is related to the social image of the nursing profession. This study aims to understand the influence of the vocation for leadership that the nursing manager has and how it can influence the work environment, through the analysis of experiences lived by health professionals with a management profile of different health environments; Methods: Qualitative study of an approximation to grounded theory using Corbin &amp; Strauss as reference, using semi-structured individual interviews as a technique, and with the participation of 10 Mexican nursing managers from second-level care hospitals; Results: The meaning of the vocation for the interviewed managers is based in the first instance on the love of the profession and the vocation to be a nurse, then on the development of leadership for decision-making in practice and is fed back with the positive effects that it generates in the work environment, helping them to better organize human resources and professional activities, and strengthening themselves with specific training on the subject and the experience acquired. ; Conclusions: An understanding model is provided about the phenomenon where two central categories were identified, the first central category is the "Management vocation and natural nursing leadership" which is the basis; The second central category is the "Explanation and influence of the managerial vocation, natural leadership and work environment in nursing". Two connection categories were also created; the connection category one "Motives, meaning, and practical vocation of managerial nursing" and the connection category two "Description of the managerial vocation, natural leadership, and work environment", said connection categories emanate from the central category one, to connect with the central category two, which contains the interaction of the managerial vocation, natural leadership, and work environment in nursing.

Electric Vehicles (EVs) are increasing the interdependence of transportation policies and the electricity market. EMMEV (Electricity Market Model with Electric Vehicles) is an experimental agent-based model that analyses how carbon reduction policy in transportation may increase number of Electric Vehicles and how does that would influence on the electricity price. Agents are ESCOs (Energy Service Providers) which can distribute fuels and their objective is to maximize their profit. In this paper, EMMEV is used to analyze the impacts of the LCFS (Low Carbon Fuel Standard), a performance-based policy instrument, on electricity prices and EV sales. The agents in EMMEV/regulated parties in LCFS should meet a certain CI (Carbon Intensity) target for their distributed fuel. In case, they cannot meet the target, they should buy credit to compensate for their shortfall and if they exceed, they can sell their excess. The results, considering the assumptions and limitations of the model, show that the banking strategy of the agents contributing in the LCFS might have negative impact on penetration of EVs, unless there is a regular Credit Clearance to trade credits. It is also shown that the electricity price as result of implementing the LCFS and increasing number of EVs has increased between 2–3 percent depending on banking strategy.

Antioxidant, anti-inflammatory and chemo-preventive features have been reported for the carotenoid diatoxanthin. Diatoxanthin is only produced by a few groups of microalgae where it functions in photoprotection. Its large-scale production in microalgae is currently not feasible. In fact, rapid conversion into the inactive pigment diadinoxanthin is triggered when the cells are removed from the high-intensity light source, which will be the case during large-scale harvesting of microalgae biomass. Zeaxanthin epoxidase (ZEP) 2 and/or ZEP3 have been suggested to be responsible for the back-conversion of high-light accumulated diatoxanthin to diadinoxanthin in low light in diatoms. Using the CRISPR/Cas9 gene editing technology we knocked out the ZEP2 and ZEP3 genes in the already commercially used marine diatom Phaeodactylum tricornutum to investigate their role in the diadinoxanthin-diatoxanthin cycle, and to determine if one of the mutant strains could function as a diatoxanthin production line. Light shift experiments proved that ZEP3 encodes the enzyme converting diatoxanthin to diadinoxanthin in low light. Loss of ZEP3 caused the high-light accumulated diatoxanthin to be stable for several hours after the cultures had been returned to low light, suggesting that zep3 mutant strains could be suitable as commercial production lines of diatoxanthin.

A correlation between Chinese traditional architecture and cultural concepts has been established to analyze the formalization of architectural and urban patterns in relation to environmental features. In this regard, we have discussed the process of standardization from architectural elements or modules related in different levels of composition and articulated around empty spaces following ancient cosmic concepts to achieve harmony with nature. The conclusions show that Chinese architectural patterns can only be understood in relation to nature, and in turn have profound environmental values from which lessons can be learned to advance towards a more sustainable architecture.

In the context of global changes, Nature-Based Solutions (NBSs) increasingly draw attention as a possible way to reduce disaster risk associated with extreme hydro-meteorological events while providing human well-being and biodiversity benefits at the same time. The PHUSICOS platform is dedicated to gather and analyse relevant NBSs used to reduce disaster risk associated with extreme hydro-meteorological events in mountainous and hilly lands. To design the platform, an in-depth review of 11 existing platforms has been performed. The platform currently references 152 literature NBS cases and is continuously enriched with demonstrator sites through the contribution of NBS community. The platform also proposes a qualitative assessment of the NBSs collected according to 15 criteria related with five ambits: disaster risk reduction, technical and economical feasibility, environment, society and local economy. This paper presents the structure of the platform and a first analysis of its content.

Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions becomes a challenge due to the stringent requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts where an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live-video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal has been implemented and assessed in a laboratory context, analyzing the model performance and QoS metrics. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% of accuracy. Also, obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.

This prospective observational cohort pilot study included 22 cats diagnosed with partial traumatic brachial plexus injury (PTBPI), aiming to explore the response of an early intensive neurorehabilitation protocol in a clinical setting. This protocol included functional electrical stimulation (FES), locomotor treadmill training and kinesiotherapy exercises, starting at the time with highest probability of nerve repair. The synergetic benefits of this multimodal ap-proach were based on the potential structural and protective role of proteins and release of neurotrophic factors. Furthermore, parametrization of FES was according to the presence or absence of deep pain. Results have shown that 72.6% (16/22) cats achieved ambulation, with 9 cats within 15 days, 2 cats until 30 days and 5 cats until 60 days. During the 4 years follow-up, there was evidence of improvement on both muscle mass and muscle weakness, in addition to the disappearance of neuropathic pain. Notably, after the 60 days of neurorehabilitation, 3 cats improved ambulation after arthrodesis of the carpus. Thus, early rehabilitation, with FES ap-plied at the first weeks after injury and accurate parametrization according to the deep pain perception, is suggestive to help in functional recovery and ambulation, reducing probability of amputation.

National heatwave plans are aimed at reducing the avoidable human health consequences due to heatwaves, by providing warnings to and improving communication between relevant stakeholders. The aim of this study was to assess the perceptions of key stakeholders within plans in Belgium and the Netherlands on their responsibilities, the partnerships, and the effectiveness of the local implementation in Brussels and Amsterdam. Key informant interviews were held with stakeholders that had an important role in development of the heatwave plan in these countries, or its implementation in Brussels or Amsterdam. Care organisations, including hospitals and elderly care organisations, had a lack of familiarity with the national heatwave plan in both cities, and prioritised heat the lowest. Some groups of individuals, specifically socially isolated individuals, are not sufficiently addressed by the current national heatwave plans and most local plans. Stakeholders reported that responsibilities were not clearly described and that the national plan does not describe tasks on a local level. We recommend to urgently increase awareness on the impact of heat on health among care organisations. More emphasis needs to be given to the variety of heat risk groups. Stakeholders should be involved in the development of updates of the plans.

The aim of this study was to verify the effects of blood flow restriction on movement velocity and muscle activity during the back-squat exercise. Methods: Twenty-four university students participated in this study. In two randomized 72-hours apart sessions, participants performed a 4-set protocol consisting of 30-15-15-15 repetitions performed at 30% of their one-repetition maximum in the back-squat exercise. In both sessions, neuromuscular function was monitored by surface electromyography (EMG) and movement velocity (mean propulsive velocity [MPV], peak concentric velocity [Vmax] and the effort index [EI]). Blood flow restriction (BFR) was applied during exercise in one of the experimental sessions with 80% of full arterial occlusion pressure over lower limbs. Results: BFR condition showed higher (p&lt;0.05) EI, peak and rooted mean square normalized EMG in set 1 compared to set 2. Similar MPV and Vmax were observed at each set for both BFR and control conditions. No significant differences were observed between conditions at any set. Conclusions: BFR did not imply changes in neuromuscular performance during low-intensity resistance training, but it might induce greater intra-series velocity loss and less activation of the muscles involved.

A rehabilitation technique for asphalt pavements with geosynthetic is the application of impregnated nonwoven geotextiles between deteriorated and new asphalt overlays. The performance investigation of impregnated geotextiles proves that they are enhancing in mechanical and hydraulic properties. Although, the installation process may cause severe impacts on these materials’ performance. During the installation, the geotextile suffers damage due to the traffic of high load vehicles, as compactors and pavers, and the friction with granular materials found under its layer or poured above it. This paper aims to investigate how the damage caused by granular materials on nonwoven geotextiles impregnated with different asphalt emulsions effect on their strength resistance and permittivity. From two types of nonwoven geotextiles: polypropylene and polyethylene terephthalate, the comparison uses geotextiles in three conditions: not impregnated, impregnated with asphalt emulsion of rapid setting, and impregnated with asphalt emulsion changed by an elastomeric polymer. Part of the samples followed the damage according to ISO 10722 procedure, placed between three different scenarios of granular materials, applying gravel, sand, and clay. After the damage process, the samples were submitted to mechanical and hydraulic properties evaluations.

A theoretical model to translate the evolution over time, in early stages, of growth and accumulation of biofilm bacterial mass is introduced. The model implies the solution of a system of differential-difference master equations. The application of an algorithm like Miller´s tree term recurrence, already known for Bessel functions of first kind, allows an exact calculation of the solutions of such equations, for a wide range of parameters values and time. For biofilm model a five term recurrence is deduced and applied in a backwards computation. A suitable normalisation condition completes the reach of the solution.

Natural rivers in urban areas bear significant potential to provide ecosystem services for the surrounding inhabitants. However, surface sealing by houses and street networks, urban drainage, disposal of waste and wastewater resulting from advancing urbanization usually lead to the deterioration of urban rivers and their riparian areas. This ultimately damages their ability to provide ecosystem services. This paper presents an innovative methodology for a rapid and low-cost assessment of the ecological status of urban rivers and riparian areas in developing countries under data scarce conditions. The methodology uses a combination of field data and freely available high-resolution satellite images to assess three ecological status categories: river hydromorphology, water quality, and riparian land cover. The focus here is on the assessment of proxies for biophysical structures and processes representing ecological functioning that enable urban rivers and riparian areas to provide ecosystem services. These proxies represent a combination of remote sensing land cover- and field-based indicators. Finally, the three ecological status categories are combined to quantify the potential of different river sections to provide regulating ecosystem services. The development and application of the methodology is demonstrated and visualized for each 100 m section of the Pochote River in the City of León, Nicaragua. This spatially distributed information of the ecosystem service potential of individual sections of the urban river and riparian areas can serve as important information for decision making regarding the protection, future use, and city development of these areas, as well as the targeted and tailor-made development of nature-based solutions such as green infrastructure.

Thermal comfort is extremely important in architecture, especially in environments with more people spending longer on studies or intellectual activities. This research describes a case study to investigate university buildings' energy and thermal performance as a part of the ANEEL program. Due to this importance, and the need to save energy in Brazilian public buildings, the ANEEL-the Brazilian Energy Electricity Regulatory Agency, launched 2016 a national program focusing on energy efficiency in public universities around the country. University offices and classrooms require high intellectual effort; thus, environmental comfort is critical for maintaining its users' physical and mental health. This study included a pre-diagnosis of the performance of the envelope, lighting, and air conditioning systems and a survey about the quality of the environments from the users' point of view. The Prescriptive Method of the Brazilian Labeling Program (PBE) for Commercial, Service, and Public Buildings (RTQ-C) assessed the building performance. Statistical analysis was applied to correlate the quality and thermal preference of the users from the PMV/PPD. The results showed a high rate of thermal discomfort in both environments of the studies, even when using air conditioning.

Empowering women and promoting gender equality is crucial for accelerating sustainable development in fragile countries, including the Democratic Republic of Congo (DRC). However, there is scarce existing knowledge or understanding of the factors determining women’s empowerment in these contexts. We aimed to assess women's empowerment and determine its associated factors in Kinshasa, DRC. We analyzed data from the 2021 Performance Monitoring Assessment (PMA) survey. A sample of 1,365 women of childbearing age was retained for this study. Twenty empowerment items related to household decision-making, contraception use, and husband/partner influence were considered. We calculated the average women’s empowerment index (aWEI), identified the women empowerment variables using principal component analysis (PCA), and determined the associated factors for the first three principal components through the performance of multivariate binary logistic regression. In Kinshasa, the overall aWEI was estimated at 0.65. It was low for household decision-making (0.34) and high for husband/partner influence domains (0.93), respectively. Three principal components were identified and named, including the absence of threats, control of sexuality, and participation in decision-making. The factors associated with these components were having internet access, being in free union with a partner, being aged 40-49 years, and residing in a non-slum area. Increasing access to information would enable women in Kinshasa to make strategic decisions about their lives, benefiting themselves and others.

Dyslipidemia presents high levels of serum cholesterol, being characterized as a risk factor for cardiovascular diseases, especially for the development of atherosclerosis. E. oleracea (OFEO), A. esculentus (OFAE), B. orellana (OFBO) and granulated (CHR) oils are rich in bioactive compounds with potential to treat changes in lipid metabolism. This study investigated the effects of treatments with oils from A. esculentus, E. oleracea, B. orellana and granules (Chronic SM®) on saturated fat-induced dyslipidemia Cocos nucifera L. The chromatographic profile showed the majority of unsaturated fatty acids in the tested oils. The quantification of tocotrienols and geranylgeraniol was obtained in OFBO and CHR. Treatments with OFEO, OFAE, OFBO and CHR were able to significantly reduce glycemia with p&gt;0.001, as well as hypertriglyceridemia, total cholesterol and LDL-cholesterol, in addition to increasing HDL-cholesterol. The treatments inhibited the formation of atheromatous plaques in the vascular endothelium of the treated rats. The obtained results suggest that the OFEO, OFAE, OFBO and CHR groups have antidyslipidemic effects and antiatherogenic activity.

Peripheral nerve injuries (PNI) can have several etiologies, such as trauma and iatrogenic interventions that can lead to the loss of structure and/or function impairment. These changes can cause a partial or complete loss of motor and sensory functions, physical disability, and neuropathic pain, what in turn can affect the quality of life. For those reasons, PNI is a major public health concern. This review aims to revisit the concepts associated with the PNI. First, the anatomy of the peripheral nerve is detailed to explain the different types of injury. Then, some of the available therapeutic strategies are explained, including surgical methods, pharmacological therapies, and the use of cell-based therapies alone or in combination with biomaterials in the form of tube guides. Nevertheless, even with the various available treatments, it is difficult to achieve a perfect outcome with complete functional recovery. This review aims to explain the urge for new approaches and to understand the methods to evaluate nerve regeneration in a One Health perspective. In vitro models followed by in vivo models are very important to be able to translate the achievements to human medicine.

This study applies several natural language processing techniques for characterizing social groups by analyzing published text in social media. The resulting computed values are proposed as features for modeling social groups and measure distances or similarities among them, along further data that could help understanding group behavior according to language usage. In this study, we have analyzed the messages published on Twitter regarding patriotism by the main political parties in Spain. The results show that lexical resources and topic modelling algorithms are useful to model different groups and serve as comparison tools to better understand the topics these groups are talking about.

We recently screened a series of new aziridines β-D-galactopyranoside derivatives for selective anticancer activity and identified 2-methyl-2,3-[N-(4-methylbenzenesulfonyl)imino]propyl 2,3-di-O-benzyl-4,6-O-(S)-benzylidene-β-D-galactopyranoside (AzGalp) as the most promising compound. In this article, we explore possible mechanisms involved in the cytotoxicity of this aziridine and evaluate its selective anticancer activity using cancer cells and normal cells from a variety of tissues. Our data show that AzGalp induces DNA damage (detected with the comet assay). Cells deficient in the DNA repair pathway nucleotide excision repair (NER) were hypersensitive to the cytotoxicity of this compound. These results suggest that AzGalp induces bulky DNA adducts, and that cancer cells lacking a functional NER pathway may be particularly vulnerable to the anticancer effects of this aziridine. Several experiments revealed that neither the generation of oxidative stress nor the inhibition of glycolysis played a significant role in the cytotoxicity of AzGalp. The combinations of AzGalp with either oxaliplatin or 5-fluorouracil slightly improved the ability of both anticancer drugs to selectively kill cancer cells. AzGalp also displayed selective cytotoxicity against a panel of malignant cells versus normal cells; the highest selectivity was observed for two acute promyelocytic leukemia cell lines. Additional preclinical studies are necessary to evaluate the anticancer potential of AzGalp.

The Pandemic in 2019 forced a digital adaptation with direct consequences on all educational stakeholders. On behalf of teachers and trainers, while many regarded these changes with some scepticism, others embraced the opportunity to integrate technology into their teaching methods and as learning resources. As translation trainers, it is essential to follow and understand the translation market. Thus, the exponential changes that digital technology has brought to this sector over the years impose constant shifts in teaching and learning methods and resources. In fact, translators require vast competencies, amongst which is the flexibility to adapt. In translation training Project-Based Learning (PBL) has been established as an essential teaching and learning method, as it has proven to foster the development of competencies as it simulates the translator's work environment. Thus, the need to adapt new strategies reinforced PBL and its benefits. PBL, however, similar to a freelance translator, places the student in the centre of the learning process, where self-regulation becomes essential, as it is necessary to analyse the market/situation and be flexible enough to adapt to the context accordingly. As of 2018-2019, technical translation courses at ISCAP have implemented PBL as their main teaching and learning method. At the same time, a study on student self-regulation began. The purpose was to understand student perception on their own self-regulation competence and its development or lack thereof after one year of PBL. Results indicate that PBL is seen as a useful simulation of the translation labour market and that it does enhance many essential competences, amongst which is student self-regulation.

The purpose of this article is to analyze urban form through the mapping of morphological indices, namely impervious surface fraction, building density, verticality, height/width ratio, roughness length, and porosity, to support urban planning in the city of João Pessoa, PB, in northeastern Brazil. The application of this study identifies and calculates such significant indices for the city's urban space from a Geographic Information System (GIS) model. The spatial indices play notable roles in climate at different scales, developing guidelines to maximize environmental quality, promote improvements to thermal comfort, minimize the urban heat island in the city of João Pessoa, and provide relevant data (considering microclimate aspects), guiding decisions related to the planning process.

Seafood is considered one of the main food allergen sources by the European Food Safety Authority (EFSA). It comprises several distinct groups of edible aquatic animals including fish and shellfish such as crustacean and mollusks. Recently the EFSA recognized the high risk of food allergy over the world and established the necessity of developing new methodologies for its control. Consequently, accurate, sensitive and fast detection methods for seafood allergy control and detection in food products are highly recommendable. In this work, we present a comprehensive review of the applications of the proteomics methodologies for the detection and quantification of seafood allergens. For that, two consecutive proteomics strategies (Discovery and Targeted Proteomics) applied for the study and control of seafood allergy are reviewed in detail. In addition, future directions and new perspectives were also provided.

Visual impairment and blindness are a growing public health problem, as they reduce the quality of life of millions of people. The management and treatment of these diseases represent a scientific and therapeutic challenge, since the different cellular and molecular actors involved in the pathophysiology are still being identified. The visual system components, particularly the retinal cells, are extremely sensitive to genetic or metabolic alterations, and immune cells activated by insults contribute to biological events that culminate with vision loss and irreversible blindness. Several ocular diseases are linked to retinal cell loss, and diseases such as retinitis pigmentosa, age-related macular degeneration, glaucoma and diabetic retinopathy are characterized by pathophysiological hallmarks that represent possibilities to study and develop novel treatments for retinal cells degeneration. Here, we present a compilation of revisited information on retinal degeneration, including pathophysiologic and molecular features, biochemical hallmarks and possible directions for novel treatments, aiming to assist as a guide for innovative research. The expansion of knowledge of the mechanistic bases of the pathobiology of eye diseases, including information on the complex interactions of genetic predisposition, chronic inflammation, and environmental and aging-related factors will allow the identification of new therapeutic strategies.

Anthocyanins are among the best-known phenolic compounds and possess remarkable biological activities, including antioxidant, anti-inflammatory, anticancer, and antidiabetic effects. Despite their therapeutic benefits, they are not widely used as health-promoting agents due to their insta-bility, low absorption, and thus, low bioavailability and rapid metabolism in the human body. Recent research suggests that the application of nanotechnology could increase their solubility and/or bioavailability, and thus, their biological potential. Therefore, in this review, we decided to provide, for the first time, a comprehensive overview of in vitro and in vivo studies on nanocarriers used as delivery systems of anthocyanins, and their aglycones, i.e., anthocyanidins alone or com-bined with conventional drugs to the treatment or management of chronic diseases.