Solid polymer electrolytes and composite polymer electrolytes serve as crucial components in all-solid-state energy storage devices. Structural batteries and supercapacitors present a promising alternative for electric vehicles, integrating structural functionality with energy storage capability. However, despite their potential, these applications are hampered by various challenges, particularly in the realm of developing new solid polymer electrolytes that require more investigations. In this study, novel solid polymer electrolytes and composite polymer electrolytes were synthesized using epoxy resin blends, ionic liquid, lithium salt, and alumina nanoparticles, and subsequently characterized. Among the formulations tested, the optimal system, designated as L70P30ILE40Li1MAl2 and containing 40 wt.% of ionic liquid and 5.7 wt.% of lithium salt, exhibited exceptional mechanical properties. It displayed a remarkable storage modulus of 1.2 GPa and reached ionic conductivities of 0.085 mS/cm at 60°C. Furthermore, a proof-of-concept supercapacitor was fabricated, demonstrating the practical application of the developed electrolyte system.

Background: Although confirmed cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been declining since late 2020 due to general vaccination, little research has been done regarding the impact of vaccines against SARS-CoV-2 in Spain in terms of hospitalizations and deaths. Objective: Our aim was to identify the reduction in severity and mortality of coronavirus disease 2019 (COVID-19) at a nationwide level due to vaccination. Methods: We designed a retrospective, population-based study to define waves of infection and to describe the characteristics of the hospitalized population. We also studied the rollout of vaccination and its relationship with the decline in hospitalizations and deaths. Finally, we developed two mathematical models to estimate non-vaccination scenarios using machine learning modeling (with the ElasticNet and RandomForest algorithms). The vaccination and non-vaccination scenarios were eventually compared to estimate the number of averted hospitalizations and deaths. Results: In total, 498,789 patients were included, with a global mortality of 14.3%. We identified six waves or epidemic outbreaks during the observed period. We established a strong relationship between the beginning of vaccination and the decline in both hospitalizations and deaths due to COVID-19 in all age groups. We also estimated that vaccination prevented 170,959 hospitalizations (CI 95% 77,844–264,075) and 24,546 deaths (CI 95% 2,548–46,543) in Spain between March 2021 and December 2021. We estimated a global reduction of 9.19% in total deaths during the first year of COVID-19 vaccination. Conclusions: Demographic and clinical profiles changed over the first months of the pandemic. Patients over 80 years old and other age groups obtained clinical benefit from early vaccination. The severity of COVID-19, in terms of hospitalizations and deaths, decreased due to vaccination.

In polymer-based dental composites, wear is a three-body wear system mainly abrasive, because of the food particles and wear products suspended in the oral cavity, which are transferred to the microcavities of the surface of the replacements. Due to this fact, the incorporation of nanodiamond as reinforcement in these polymer matrix composites, which promotes the creation of a solid lubricant tribofilm surface could be advantageous. When nanodiamond is added in contents of 0.8, 1.6 and 3.2 wt %, an increase in microhardness from 95 up to 420 %, compared to the one of neat BisGMA/TEGDMA, is observed. Additionally, the incorporation of a content of 1.6 wt % is enough to cause a diminution of ~78 % in the friction coefficient and a reduction of the specific wear rate and Archard’s coefficient of ~50 %. Nevertheless, the addition of relatively high contents reduces the effectiveness of photoinitiation and UV-curing, which is related to the scattering and absorption of UV radiation by ND.

Statistics modules are included in most university degrees, independent of the degree area. They have an important role in preparing students for the real world. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. Drawing upon data from the University College Dublin (UCD) Math Support Center (MSC) and Universidad Rey Juan Carlos (URJC), our approach aims to optimize learning experiences while advancing sustainability objectives. In this paper, we conducted a categorization of statistical concepts taught in university (based on URJC). Using this categorization, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. Building on this study, we plan to develop a suite of evidence-based sustainable educational applications and games to support undergraduate students internationally in first-and second-year statistical modules. Our findings on students’ main statistical issues contribute to the cultivation of lasting statistical literacy among students. This research advances the sustainability agenda within statistical education.

The text examines the assessment of learning in science and the use of technologies like Scratch to enhance this process. Assessment is crucial for measuring progress and guiding teaching, especially in science where it fosters scientific skills and understanding. The study focuses on third-year secondary education students, evaluating the impact of Scratch on their learning compared to a gamification approach. Scratch, developed by MIT, is effective in interactive teaching and improves academic performance and student motivation. The research used an experimental design with a control group (gamification) and an experimental group (Scratch), measuring acquired knowledge through pretests and posttests. Results show that both groups significantly improved their knowledge, although the control group had a higher baseline initially. Students valued collaboration and playful learning. However, they faced technical challenges and highlighted the importance of teamwork. The study concludes that Scratch has great educational potential, suggesting improvements such as redesigning activities and increasing work sessions to maximize its effectiveness in learning and student motivation.

Heat waves represents a major concern for the tourism industry in the Mediterranean area. Therefore, it is necessary to deepen the study of the influence of high temperatures and their effects on tourist behavior. This research aims to develop a structural model that allows measuring how heat waves affect the behavior of external tourist demand in coastal destinations. The results are useful for the design by tourist destinations of adaptation measures to climate change. The proposed hypotheses have been contrasted using non-linear structural equations (SEM), estimated with data from the National Institute of Statistics on external demand in Spain. The results confirm lower tourist flows with the increase in high temperatures to the coasts of the Spanish Mediterranean area from traditional source markets, such as the United Kingdom. Furthermore, the tourist flow to the Balearic Islands decreases with high temperatures.

The aim of this work was to classify the business incubators in Spain according to the four phases of the startup’s incubation process. Considering that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the business incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis has been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors. Finally, the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3, named activity monitoring and control, was related to phase 3 or basic incubation variables. Cluster analysis facilitates the grouping of business incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small sized business incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factors 1 and 2. Factor 3, although positive, it is susceptible to improvement. They are the largest group of business incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

Abstract: This article aims to better understand the mechanisms that connect climate change perceptions and general willingness to engage in pro-environmental behavior using Spanish cross-sectional data (N = 403). To do this, we first developed and validated the General Willingness for Environmental Behavior Scale (GWEBS), which includes the classical approach of voluntarily doing new actions but also actions implying not doing things (degrowth) and actions forced by social constraints. The exploratory and confirmatory factor analysis showed a good fit for the one-factor structure, which had adequate validity based on their relationship with other variables. Additionally, the GWEBS distinguished between women and men, left- and right-oriented people, and people who belonged to pro-environmental groups and people who did not. In the second place, we tested the parallel mediator role of eco-anxiety and trust in science in the relationship between climate change perceptions and the GWEBS. The results showed that eco-anxiety, fully, and trust in science partially mediated such a relationship, making them crucial to mobilize the intention to act following the perception. This study contributes to our understanding of the psychological mechanisms that eventually drive pro-environmental behaviors and provides a clear direction for future research.

The penetrability and directivity of ultrasound in different media is of interest in engineering and medical applications (imaging, nondestructive testing, sonochemistry, among others). The nonlinearity of a liquid can be used in the parametric antenna framework to generate low-frequency components with particular features from several ultrasonic signals at the source. Bubbly liquids are dispersive liquids in which a small amount of tiny gas bubbles leads to the increase of the nonlinear parameter of the media over certain frequency ranges. Parametric antenna applied to this huge nonlinear media gives rise to low-frequency components with relatively small intensity at the source. The evolution of a low-frequency component (difference-frequency component obtained from two primary signals) during its propagation in a bubbly liquid is somehow unknown. It is thus interesting to analyse its characteristics to establish whether this component can benefit from the quality of its own frequency and from the primary frequencies in terms of directivity and penetrability into the medium. It must be noted that no such study in bubbly liquids exists in the litterature, but only for homogeneous media. To this end, several numerical models developed previously are used here to analyse the difference-frequency component obtained from a parametric antenna emitting from two ultrasonic signals at the source in one and two-dimensional domains. These models allow us to observe the behavior of this frequency component. An angle that measures the directivity of a beam is also defined. Our results show a point hardly found in the literature: the high directivity and the huge penetrability of the secondary beam associated to the difference-frequency component into the bubbly liquid, compared to the same frequency signal excited directly from the source in the bubbly liquid and to the parametric acoustic array in homogeneous fluids.

In the rapidly evolving landscape of the AI era, the measurement of Computational Thinking ability among Computer Science (CS) University students is of paramount importance. This study introduces UniCTCheck, a novel method designed to assess the main components of Computational Thinking in CS students. Utilizing two key instruments, namely the web application CTScore and the psychometric scale CTProg, this research aims to precisely evaluate seven core components of Computational Thinking and six programming concepts skills essential for CS students. The study, conducted at Rey Juan Carlos University and Atlantic Technological University Galway, involved a diverse sample of students from different year levels and program specializations. Through a rigorous research design, including sampling strategies and data collection tools, this study seeks to address critical research questions related to measurement of variations in students' Computational Thinking and programming skills by gender, university level, and location. By shedding light on the significance of Computational Thinking and programming in the educational realm, this research contributes to the existing literature and underscores the essential role of computational skills in the modern era.

Objective. To test the hypothesis that a session of unilateral tSMS over the dominant primary motor cortex (M1) in healthy subjects produces a transient decrease in manual dexterity. Methods. A triple-blinded randomized control trial was conducted in 40 healthy participants who were allocated to real- or sham-tSMS group. Each participant underwent one session of tSMS and were assessed before, immediately after, 15 minutes, and 40 minutes after stimulation. Outcome measures were Finger Tapping Test (FTT), 5-seconds FTT, nine Hole Peg Test, and the hand grip assessment. Results: Significant differences were found between groups 15 minutes after stimulation in favor of the tSMS group in the FTT (2.2 ± 0.99; CI= .18-4.22; d= .84p=.034), and 5-second FTT (4.2 ± 1.98; CI= .199-8.2, d= .68; p=.04). In the intragroup analysis, a significantly lower number of taps 15 minutes after stimulation was observed in sham group (3.3 ± 1.01; CI= .47-6.13; d= .42; p=.015), but not in the real stimulation group. Conclusion: A unilateral session of tSMS in the M1 of the dominant hemisphere of healthy individuals does not reduce manual dexterity or grip strength. This technique could have benefits on the motor performance of the arm contralateral to the stimulated motor cortex

While digitization can make the health industry faster and more efficient, there are many financial, social and organizational obstacles and barriers to its implementation. This article offers a systematic review of the main troubles detected from the literature review. Also there is a proposal of new kind of restrictions to pay attention. Finally, its offer an heterodox reading about the problem analyzed.

Recommender systems in education are becoming more widespread, typically focusing on recommending courses or study materials. This study proposes a machine learning approach to recommend a university degree based on high school and university standardised test results, incorporating students' socioeconomic information as input variables. The objective is to develop a tool for students’ decision-making, supporting the sustainable development goal of Quality Education by providing a data schema to maximise the likelihood of a successful match between the student's profile and the academic program. With its focus on equity in education, this study provides a data-driven approach to assist students in selecting suitable university degrees, aiming to improve educational outcomes and inspire a more equitable education system.

Introduction:Few robust studies have analyzed association between cognitive tests and the marital status of Mild Cognitive Impairment (MCI) group with ADNI dataset. To test the hypothesis that Rey Auditory Verbal Learning test (RAVLT) cognition performance with marital status is associated with greater odds of MCI group than either RAVLT independently, we used TADPOLE data to evaluate cross-sectional associations between RAVLT performance in immediate response, learning, forgetting, and perception of forgetting with marital status and MCI. Methods: Subjects with MCI and Normal Cognition were included. Logistic regression models indicate associations between four RAVLT subgroups (low and high performance of immediate response, immediate response with learning, performance of immediate response with learning and forgetting, performance of immediate response with learning, forgetting and perception of forgetting) and MCI group. Models adjust for age, sex, race, marital status, ethnicity, education, APOE4 genotype, hippocampus, whole-brain, ventricles and ICV. Results: The sample (n=6560) had a mean age of 77 / 67 years, 44% were female, 58% in MCI group. Only all RAVLT subgroups test with age 61 to 70(OR 0.26, 95% CI 0.15-0.45), age 71 or older(OR 0.07, 95% CI,0.04-0.12), race:black/african american(OR 0.13, 95% CI 0.03-0.52)race:more than one(OR 0.05, 95% CI 0.01-0.24), marital status:never married(OR 0.2, 95% CI 0.12-0.34). Conclusion: Studies are needed to evaluate other cognitive test with missing data within TADPOLE dataset as modifiable risk factor for MCI.

This study assessed the hydrological performance and runoff water quality of 12 green roof (GR) modular systems located at the Universidad de los Andes campus (Bogotá, Colombia). Based on 223 rainfall events spanning a 3-year period, average rainfall retention was 85% (SD = 25%). T-tests, Welch Test, multiple linear regressions and correlation analysis were performed in order to assess the potential effect of air temperature, substrate type, vegetation cover, relative humidity, antecedent dry weather period (ADWP), rainfall duration and rainfall maximum intensity. In some cases, GR design variables (i.e. growing media and type of vegetation) were found to be significant for describing rainfall retention efficiencies and, depending on the GR type, some hydrological variables were also correlated with the rainfall retention. Rainfall and GR runoff were monitored for Total Kjeldahl Nitrogen (TKN), Nitrates, Nitrites, Ammonia, Total Phosphorus (TP), Phosphates, pH, Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Color, Turbidity, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Coliforms, metals and Poliaromatic Hydrocarbons (PAHs). The results obtained confirmed that GR systems have the ability to neutralize pH, but are source of the rest of the aforementioned parameters, excluding PAHs (with concentrations below detection limits), Ammonia, TSS, Se and Li, where differences with reference values (rainfall and plastic panel runoff) were not statistically significant. Substrate type, event size and rainfall regime are relevant variables for explaining runoff water quality.

This study investigates the impact of Artificial Intelligence (AI) on traditional firms, specifically examining how scalable network properties and the integration of Environmental, Social, and Governance (ESG) considerations affect financial margins, sustainability, and bankability. The research addresses the core question of how AI investments can drive economic value by enhancing EBITDA and financial stability while aligning firms with sustainability goals. Using advanced network theory and multilayer models, the study reveals that AI-driven scalability significantly improves a firm's financial performance, making it more attractive to investors and financial institutions. Additionally, the integration of ESG factors further enhances operational efficiency, market valuation, and long-term financial stability. The study introduces an innovative "with-or-without" analysis to quantify the comparative benefits of AI and ESG integration, underscoring the role of these technologies in driving sustainable growth and addressing bankability concerns in traditional firms. This comprehensive approach offers new insights into the evolving dynamics of AI, ESG, and corporate finance.

Measuring host communities' perceptions and attitudes towards tourism development has been increasingly common since the mid-1970s. The greater the growth of the tourism industry worldwide, the more relevant it has become to assess the impact of tourism activity on the local residents. In this paper we present the results of a study carried out in two EU countries highly dependent on tourism act though at a different stage of development. Our findings are based on qualitative and quantitative data obtained via a questionnaire survey designed in pre-covid 19 times to analyze the perceptions and attitudes of tourism college students from Croatia and Spain, today’s tourism employers and employees, towards tourism development in sun and sea desti-nations. Our aim is to contrast the hypothesis that the nationality of our sample is a significant variable when evaluating the socioeconomic and environmental impact of the development of the tourism industry. Croatia’s workforce, the most highly dependent on the EU travel and tourism industry show to be much more aware of the negative impacts of tourism development than their Spaniards counterparts; showing a tourism workforce more reluctant to further tourism development.

Greenflation or inflation for green energy transition in Europe, it becomes a structural problem of new scarcity and poverty, because the Green Deal and its fiscal and monetary policies. In this paper, it is paid attention to the Green financial bubble and the European greenflation paradox: in order to achieve greater future social wellbeing, due to a looming climate risk, present wellbeing and wealth is reduced, causing a real and ongoing risk of social impoverishment. According to the European Union data, it is going to show the relations between green transition (emissions, tax, debt, credit boom, etc.), GDP and inflation. As many emissions are reduced, there is a decrease of GDP (once deflated) and GDP per capita, evidencing social deflation, which in turn means more widespread poverty and a reduction of middle-class. Also, there is a risk of a green-bubble, like in the Great Recession of 2008 (but this time supported by the European Union) and possible stagflation. To analyze this problem, it is used here some econometric tools, but under the theoretical support of heterodox approaches, especially the Austrian Economics and the New-Institutional Schools.

Obesity is a risk factor for the development of gestational diabetes mellitus (GDM). However, the most optimal type of nutritional intervention to prevent GDM in high-risk women is not clearly defined. This study investigates if nutritional treatment based on the Mediterranean diet (MedDiet) before 12th gestational week (GW) in women at high risk due to a body mass index (BMI)≥25kg/m2, reduces the rate of GDM and metabolic syndrome (MetS) at 3 years postpartum. We performed a post-hoc analysis of the San Carlos Gestational Prevention Study. A total of 735 women with BMI≥25kg/m2 were evaluated between 2015-2018, 246 in standard diet control group (CG) and 489 in MedDiet intervention group (IG). The rate of GDM was significantly lower in IG compared to CG (25.1%vs31.7%;p=0.037). Postnatal follow-up was completed by 141 women in CG (57%) and 312 women in IG (64%). At 3 years postpartum, we observed a reduction (relative risk 95% confidence interval) in the rates of impaired fasting glucose (IFG) (0.51 (0.28-0.92);p=0.019), obesity (0.51 (0.28-0.92),p=0.041), waist circumference (WC)≥89.5cm (0.54 (0.31-0.94);p=0.022) and MetS (0.56 (0.33-0.94);p=0.003). MedDiet reduces the rate of GDM and postpartum MetS in women with BMI)≥25kg/m2, suggesting that its implementation should be routinely recommended from the first GWs.

In this article the methodology for the determination of the theoretical gamma spectrum originated by applying DGNAA (delayed gamma neutron analysis activation) techniques for the elemental analysis of ash from thermal power plants is exposed. This is a study must be prior to the experimentation in order to define the parameters of the test to obtain the optimal conditions for the detection of each element present in the sample.

The building blocks of a scientific facility based on particle beams comprise magnets and electro-magnetic devices. The design of an overall accelerator usually imposes a demanding accuracy on their exact position and orientation. Their non-geometrical functional features are frequently either not clearly defined – what is the « magnetic axis » of a magnet –, or not explicitly used along their lifecycle. Improving the process to establish and use these functional features would contribute to meeting demanding challenges. The European Spallation Source (ESS) is aiming at providing a powerful proton linear accelerator and a target system to produce pulsed neutrons. The challenging complex design and integration yielded to introducing a tool for all stakeholders along the lifecycle: the "situation features", as defined in ISO GPS (Geometrical Product Specifications) standards. This paper deals with the beyond-mechanics non-geometrical use cases and generalizes the use of the association operation to theoretically exact features. The examples of the functional specification, fiducialization (measure of the real features with respect to external marks) and installation phases of quadrupole magnets is developed. Perspectives of generic use are highlighted.

Androgens are key for pubertal development of the mammalian testis, a phenomenon tightly linked to Sertoli cell maturation. In this review, we discuss how androgen signalling affects Sertoli cell function and morphology by concomitantly inhibiting some processes and promoting others that contribute jointly to the completion of spermatogenesis. We focus on the molecular mechanisms that underlie AMH inhibition by androgens at puberty, as well as on the role androgens have on Sertoli cell tight junction formation and maintenance and, consequently, on its effect on proper germ cell differentiation and meiotic onset during spermatogenesis.

(1) The objective of this study is to describe and compare the levels of physical activity, preferences for leisure-time physical activity and the frequency of non-sedentary behaviors of Portuguese, Italian and Spanish students attending, respectively, higher education in Portugal, in Italy and Spain; (2) Methods: 1354 Portuguese, Spanish and Italian students (21.2 ± 2.9 years) participated in the study. An online questionnaire was used to collect data and a priori power analysis statistical procedures were used using G∗Power (3.1.9.7) and one-way Anova; (3) Results: The highest levels of sedentary lifestyles are found among Spanish students, followed by the Portuguese and lastly the Italians. Regarding the levels of physical activity Spanish students perform more minutes of low and moderate activity compared to Italians and Portuguese. Italians students are the ones who perform more vigorous activity; (4) Conclusions: We can conclude that Spanish students have a higher level of sedentary lifestyle with the majority of physical activity being low and moderate, while Italians are those who have more time spent on vigorous physical activity and naturally a lower level of sedentary lifestyle. However, it is worth highlighting that all three countries reach the minimum levels of physical activity recommended by the WHO.

Gestational diabetes mellitus (GDM) pathophysiology comprises clinical and genetic factors. In fact, GDM has been associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT), 255 (16.1%) with GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed by IPLEX Mass ARRAY PCR selecting 110 SNPs based on literature references. The SNPs showing the strongest likelihood of GDM development were the rs10830963, rs7651090 and rs1371614 in CAU and rs1387153 and the rs9368222 in LAT. Clinical variables including age, pre-pregnancy body mass index and fasting plasma glucose (FPG) at 12 gestational weeks predicted the risk of GDM (AUC 0.648, 95%CI 0.601-0.695 in CAU; AUC 0.688, 95%CI 0.628-9.748 in LAT) and adding the SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95%CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women. An RCT is underway to demonstrate its usefulness

For their speed in data processing, low heights and cheapness, patch antennas are important to 5G networks. While there have been improvements in the area of bandwidth and size reduction; however, there are still problems that need to be fixed with regards achieving high data rates as well as wideband operation and compact sizes for 5G applications. In the coming years researchers should concentrate on materials optimization and feeding methods so that they can work efficiently at shorter wavelengths for next-generation systems while still covering all necessary bands.

Animal communication signals are regulated by multiple hormonal axes that ensure appropriate signal targeting, timing, and information content. The regulatory roles of steroid hormones and many peptide hormones are well understood and documented across a wide range of vertebrate taxa. Two recent studies have reported a novel function for leptin, a peptide hormone central to energy balance regulation: regulating communication signals of weakly electric fish and singing mice. With only limited evidence available at this time, a key question is just how widespread leptinergic regulation of communication signals is within and across taxa. A second important question is what features of communication signals are subject to leptinergic regulation. Here we consider the functional significance of leptinergic regulation of animal communication signals in the context of both direct and indirect signal metabolic costs. Direct costs arise from metabolic investment in signal production, while indirect costs arise from the predation and social conflict consequences of the signal’s information content. We propose a preliminary conceptual framework for predicting which species will exhibit leptinergic regulation of their communication signals and which signal features leptin will regulate. This framework suggests a number of directly testable predictions within and across taxa. Accounting for additional factors such as life history and reproductive strategies will likely require modification or elaboration of this model.

The actin cytoskeleton is crucially important to maintenance of cellular structure, cell motility and endocytosis. Accordingly, bacterial pathogens often co-opt the actin-restructuring machinery of host cells to access or create a favorable environment for their own replication. The obligate intracellular organism Chlamydia trachomatis and related species exemplify this dynamic: by inducing actin polymerization at the site of pathogen-host attachment, Chlamydiae induce their own uptake by the typically non-phagocytic epithelium they infect. The interaction of chlamydial adhesins with host surface receptors has been implicated in this effect, as has the activity of the chlamydial effector TarP (translocated actin recruitment protein). Following invasion, C. trachomatis dynamically assembles and maintains an actin-rich cage around the pathogen’s membrane-bound replicative niche, the chlamydial inclusion. Through further induction of actin polymerization and modulation of the actin-crosslinking protein myosin II, C. trachomatis promotes egress from the host via extrusion of the inclusion. In this review, we present the experimental findings that inform our understanding of actin-dependent chlamydial pathogenesis, discuss lingering questions, and identify potential avenues of future study.

The severity of forest fires derived from remote sensing data for research and management has become increasingly widespread in the last decade, where these data typically quantify the pre- and post-fire spectral change between satellite images on multi-spectral sensors. However, there is an active discussion about which of the main indices (dNBR, RdNBR or RBR) is the most adequate to estimate the severity of the fire, as well about the adjustment model used in the classification of severity levels. This study proposes and evaluates a new technique for mapping severity as an alternative to regression models, based on the use of the maximum likelihood estimation (MLE) automatic learning algorithm, from GeoCBI field data and spectral indices dNBR, RdNBR and RBR applied to Landsat TM, ETM+ Images, for two fires in central Spain. We compare the severity discrimination capability on dNBR, RdNBR and RBR, through a spectral separability index (M) and then evaluated the concordance of these metrics with field data based on GeoCBI measurements. Specifically, we evaluated the correspondence (R²) between each metric and the continuous measurement of fire severity (GeoCBI) and the general precision of the regression and MLE models, for the four categorized levels of severity (Unburned, Low, Moderate, and High). The results show that the RBR has more spectral separability (average between two fires M = 2.00) that the dNBR (M = 1.82) and the RdNBR (M=1.80), additionally the GeoCBI has a better adjustment with the RBR of (R² = 0.73), than the RdNBR (R² = 0.72), and dNBR (R² = 0.71). Finally, the overall classification accuracy achieved with the MLE (Kappa = 0.65) has a better result than regression models (Kappa = 0.58) and higher accuracy of individual classes.

Calicotome villosa is a eurioic legume with broad distribution in the south of Europe. It can grow in almost any type of soils as well as in humid and dry and nutrient deficient ecosystems. The broad distribution and eurioic nature of C. villosa may be attributed to its ability to establish symbiotic associations with plant growth promoting (PGP) bacteria housed in the nodules and rootless. This study examined legume-microbe symbiosis of C. villosa growing in two contrasted locations, hill top with high sun irradiance and drought; and a valley bottom, with low level or radiation and sufficient soil humidity for plant growth. Calicotome villosa adult plants established symbiotic in-teractions with bacteria in six genera, Pseudomonas, Stenotrophomonas, Bacillus, Paenibacillus, Brevicacterium and Rhizobium as well as one uncultured bacteria. Plants growing in the hill top had associated lower bacterial richness than those grown at the valley bottom. All strains were drought tolerant and produced siderophores, IAA, HCN and NH3 that stimulated plant performance in both, C. villosa plants and other four legumes commonly present in the understory of the shrubs communities The legumes’ capacity to selectively host symbiotic bacteria that enhance plant survival in harsh conditions partly accounts for the diverse partnerships between C. villosa plants and their symbionts, ultimately explaining the wide distribution of this plant species.

This study aimed to optimize the bioelectricity production process using a vinasse solution through the application of Plackett-Burman and Box-Behnken designs. An electrochemical cell was constructed using Arduino to measure the potential difference between the anode and cathode immersed in the vinasse solution, a byproduct of wine production containing organic compounds and ions that undergo redox reactions. The Plackett-Burman design identified the most influential variables among eight previously selected, including vinasse concentration, agitation, and yeast, which positively affected millivolt production, while temperature showed a negative correlation. Based on these results, the Box-Behnken design was used for process optimization, varying parameters such as concentration, stirring, and sodium chloride. Response surface graphs demonstrated the relationship between these variables and millivolt production. The findings indicate that higher agitation levels, lower concentrations of vinasse, and the addition of sodium chloride can enhance bioelectricity generation. The study provides insights into the bioelectricity production process from vinasse, contributing to the understanding and potential for sustainable energy generation. The methodology involving Arduino-based measurement and the utilization of experimental designs offers a systematic approach to optimize bioelectricity production from vinasse.

Chromatographic separation is a critical technique in the manufacturing processes of both chemical products and biopharmaceuticals. Its principle relies on exploiting the differences in distribution between the stationary and mobile phases to achieve the separation of mixtures. The precision of substance concentration during separation directly impacts the quality and usability of the final product. Therefore, the development of an effective and precise separation control technique has long been a vital concern in the field of chromatographic separation control. Currently, the employment of Simulated Moving Bed (SMB) technology for chromatographic separation, which allows for continuous feed, has been recognized as a cutting-edge technique. SMB is a continuous process technology that enhances the efficiency of adsorbents within the bed. This sequential multi-column SMB technology not only increases production capacity but also reduces the consumption of solvents and water. It is acknowledged as one of the cleanest manufacturing technologies in the biopharmaceutical industry. However, multi-column SMB involves various variables such as flow rates in multiple sections and valve switching times, rendering its system control highly complex. Unlike traditional control objectives that aim to minimize control output errors, the control objective of SMB is to achieve a specific proportion of substance concentration. Consequently, designing and implementing traditional control theories for SMB is challenging, leading to SMB systems largely being controlled based on simple PLC controls. Moreover, these controls are often applicable only to single or a few-column SMB setups, limiting the effectiveness of high-capacity applications. To achieve effective control of SMB, this study employs an adjustable intelligent fuzzy controller with a structure like an approximate neural network (NN) for SMB control research. Simulation results demonstrate that the intelligent controller effectively achieves desirable control outcomes for the SMB system.

In this paper we try to demonstrate that the classical model of certainty factos for dealing with innacurate knowledge can be efficiently implemented in a quantum environment. For this, we assume that certainty factors are strongly correlated with the quantum probability. We first explore the certainty factors approach for inexact reasoning from a classical point of view. Next, we introduce some basic aspects of quantum computing, and we pay special attention to quantum rule-based systems. We then build a use case: an inferential network to be implemented in both, the classical approach and the corresponding quantum circuit. Both implementations have been used to compare the behavior of the classical and the quantum approaches when confronted with the same hypothetical case. We analyze three different situations: (1) Only Imprecision (which refers to inaccuracy in declarative knowledge or facts) is present in the use case, (2) Only Uncertainty (which refers to inaccuracy in procedural knowledge or rules) is present in the use case, and (3) Both Imprecision and Uncertainty are present in the use case. Finally, we analyze the results to reach a conclusion about the eventually intrinsic probabilistic nature of the certainty factors model and to pave the way for future quantum implementations of this method for handling inaccurate knowledge.

Encouraged by the administration the gentrification process has been useful in economic terms for the reactivation of socio-cultural fabrics of historic urban spaces in decline. What was initially considered an advantage has led to the touristification of historic centres, and in turn to the alter-ation of their original use. In these settings, the demographic void caused by increasingly shunning local identity has combined with pressure from excessive tourism and the obsolescence of heritage protection bodies in charge of conservation. Given the crisis affecting the definitions of the current system, this study aims to review the envi-ronmental agents of heritage value in relation to the processes of touristification and gentrification. Data obtained from different methodologies are analysed using a multidisciplinary database, a model which enables the analysis of the relevant information from the different interacting fields. The case study focuses on the historic town centre of Seville specifically between 2015 and 2020. Elements are defined as indicators for these processes and the analysis of the case study will com-prise the main results of this research.

This paper investigates the effect of Fe contamination on the microstructure and mechanical properties of Al-7Si-0.7Mg-Fe2.5 alloy processed by Laser Powder Bed Fusion (LPBF) and heat treated in two different conditions: (1) Solution Heat Treatment (SHT) at 520 °C, followed by artificial ageing at 160 °C (T6), and (2) Direct Artificial Ageing of the as-printed material at 160 °C (DAA). Microstructural characterization was carried out by Optical Microscopy (OM), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Transmission Electron Microscope (TEM). Mechanical characterization was carried out by tensile tests at room temperature. The formation of fine AlSiFe phases such as α-AlFeSi, β-AlFeSi, and π-Al8Si6Mg3Fe had no deleterious effect on the mechanical properties compared to previous studies for AlSIMg alloys without Fe. However, compared to the as-printed condition, the T6 heat treatment decreased the ultimate tensile strain significantly, while the elongation to the fracture presented a slight improvement.

Legumes are a diverse and important group of plants that play a vital role in agriculture, food security, and environmental sustainability. Rhizobia are symbiotic bacteria that form nitrogen-fixing nodules on legume roots, providing the plant with a valuable source of nitrogen. Phenolic acids are a group of secondary metabolites produced by plants that have a wide range of biological functions, including defense against pests and diseases, tolerance to abiotic stresses, and nutrient uptake. In the context of climate change and the imperative for sustainable agriculture, this study delves into the dynamic responses of legume species to varying light intensities and their intricate interactions with soil microorganisms. We investigated the impact of light intensity and rhizobial inoculation on the biomass, nitrate reductase, acid phosphatase, and production of phenolic acids in the roots of four legume species, Trifolium repens, Vicia sativa, Ornithopus compressus, and Coronilla juncea. Plants were grown under three light intensity regimes (low, medium, and high) and inoculated with either rhizobia or a non-inoculated control. The results highlights that shaded-light-adapted species, T. repens and V. sativa, increased root exudate production when exposed to high light intensity. This response aligns with their mining strategy, effectively allocating resources to optimize nutrient acquisition under varying conditions. In contrast, species hailing from well- illuminated environments, O. compressus and C. juncea, displayed distinct strategies by significantly increasing biomass under high irradiance, capitalizing on the available light and nutrients. The mining strategy of legumes emerged as a central theme, influencing biomass production, nitrogen dynamics, and enzymatic activities. The strong correlations between biomass and total nitrogen accumulation underscore the role of the mining strategy in efficient nutrient acquisition. Inoculated plants, which rely more on biological nitrogen fixation (BNF), exhibited lower δ15N values, indicative of a successful mining strategy to acquire and utilize atmospheric nitrogen. Enzymatic activities and phenolic acids exhibited significant interspecies variations, reflecting the adaptability of legumes to different light conditions. The findings of this study could be used to develop new strategies for improving legume stress tolerance, nutrient uptake capacity, and rhizosphere health.

Objective: To identify risk factors(RF) related to abnormal glucose regulation(AGR) 3 years postpartum according to 3-month-postpartum glucose status. Research design: Normoglycemic pregnant women of the St. Carlos Gestational Study included before gestational week 12, during 2015-2017. Of 3,036 eligible women, 2529 were followed-up until delivery: 1400 participated in postpartum follow-up. AGR defined as fasting serum glucose (FSG)>5.6 mmol/L and/or HbA1c >5.7% (39 mmol/mol) and/or 2h-SG ≥140/mg/dL after 75-g OGTT. 12-modifiable and 3-unmodifiable RF were analyzed for associations with glycemic changes. Reinforcement of Mediterranean Diet adherence was provided to all women at the postpartum visit by a dietitian Results: 137/1400(9.8%) women presented AGR 3 years postpartum, 27/137(19.7%) also had at 3 months, whereas 110/137(80.2%) had not. The remaining 1,263(90.2%) women were normoglycemic 3 years postpartum, 1180/1263(84.3%) were at 3 months, while 83/1263(6.08%) had AGR and became normoglycemic. Women with GDM were more likely to progress to AGR 3 years postpartum (OR:1.60[1.33-1.92]) and less likely to remain normoglycemic (OR:0.22[0.15-0.33]) versus non-GDM women. Having >2/3 unmodifiable RF was associated with a reduced rate of maintained normoglycemia (OR:0.56[0.39-0.80]) and an increased risk of progression to AGR (OR:1.90[1.28-2.83]). Having >5/12 modifiable RF was associated with a reduced rate of maintained normoglycemic (OR:0.74[0.51-0.99]) and reversion of AGR (OR:0.49[0.25-0.97]), an increased progression to AGR (OR:1.40[1.00-2.09]), and persistence of AGR (OR:2.57[1.05-6.31]). Pre-gestational BMI≥25kg/m2 (OR:1.80[1.19-2.71]), post-delivery weight gain (OR:2.22[1.10-4.48]), and waist circumference >89.5cm (OR:0.54[0.36-0.79]), (all p<0.05) were the main modifiable RF. Conclusions: RF related to an increased probability for 3-year-postpartum AGR despite 3-month normoglycemia were identified, potentially useful when designing personalized strategies for pregnant women, directed towards minimizing unfavorable outcomes.

This study develops a structure for mapping native vegetation in a transition area between Brazilian Cerrado and Atlantic Forest from integrated spatial information from the Sentinel-1 and Sentinel-2 satellites. Most studies use this data separately, however, the integrated use of optical sensors with Synthetic Aperture Radar (SAR) sensors can improve the methodology for classifying land use and land cover (LULC). The fusion of Sentinel-1 and Sentinel-2, for example, can increase the accuracy of mapping algorithms, using complementary information, such as spectral, backscattering, polarimetry, and interferometry. The study area comprises the Lobo Reservoir Hydrographic Basin, which is part of an environmental conservation unit protected by Brazilian law and with significant human development. LULC were classified, using the random forest deep learning algorithm. The classifying attributes were backscatter coefficients, polarimetric decomposition, and interferometric coherence for radar data (Sentinel-1), and optical spectral data, comprising bands in the red edge, near infrared, and shortwave infrared (Sentinel-2). The attributes were evaluated in three settings in which the SAR and optical data were evaluated separately (C1 and C2, respectively) and in an integrated manner (C3). The study found greater accuracy for C3 (96.54%), an improvement of nearly 2% compared to C2 (94.78%) and more than 40% in relation to C1 (55.73%). The classification algorithm encountered significant challenges in identifying wetlandsin C1, but performance improved in C3, enhancing differentiation by stratifying a greater number of classes during training and facilitating visual interpretation during sampling. Accordingly, the use of SAR and optical data becomes an alternative to optimize LULC mapping in tropical regions, due to the limited influence of atmosphere on images in the microwave range.

The use of fuel material and different sources of ignition causes unwanted fires, producing and spreading in different spaces. Fire fighting. systems are measures taken to minimize the effects of fire. This struggle is not only on land, but also in the maritime world, through maritime security that has become a very important element for the International Maritime Organization (IMO). Therefore, maritime accidents caused by fire are one of the challenges to be taken into account, because they require immediate control and response. This article presents a historical interpretation of the concept of maritime safety through first responders on ships. It will be demonstrate how the technological advances of such equipment have been very important for their arrival on ships. In addition, the article reveals the legislative changes of International Convention for the Safety of Life at Sea (SOLAS), which reflects the IMO requirements to prevent fire risks on board, requiring a reading of the primary documents. Finally, the importance of the evolution of first intervention equipment for safety on board has been shown.

Accelerated degradation tests (ADT) are widely used in the manufacturing industry to obtain information on the reliability of components and materials, through degrading the lifespan of the product by applying an acceleration factor which causes damage to the material. The main objective is to obtain fast information which is modeled to estimate the characteristics of the material life under normal conditions of use and to save time and expenses. The purpose of this work is to estimate the lifespan distribution of gold nanoparticles stabilized with lipoic acid (GNPs@LA) through accelerated degradation tests applying sodium chloride (NaCl) as an acceleration factor. For this, the synthesis of GNPs@LA was carried out, a constant stress ADT (CSADT) was applied, and the non-linear Wiener process was proposed with random effects, error measures and different covariability for the adjustment of the degradation signals. The information obtained with the test and analysis allows us to obtain the life distribution in GNPs@LA, the results make possible to determine the guaranteed time for a possible commercialization and successful application based on the stability of the material. In addition, for the evaluation and selection of the model, the Akaike and Bootstraping criteria were used.

Colombia is the world's leading producer of mild washed arabica coffee and produces 12.6 million bags of green coffee, but at the same time 784,000 tons of waste biomass are dumped in open fields, of which only 5% is recovered or used. The objective of this project was to evaluate the production of platform chemicals from these coffee wastes. To achieve this, biomass characterization was carried out using proximate analysis, ultimate analysis and structural analysis. Hydrothermal valorization was carried out at a temperature range of 120-180 °C (LHW) and 180-260 °C (HTC) for one hour, the platform chemicals obtained were quantified by HPLC-IR, monitored by pH and conductivity, and the solid fraction was characterized by monitoring the functional groups in IR spectroscopy, and elemental analysis. Hydrolysis processes were obtained from 150 °C, production of platform chemicals from 180 °C and maximum concentration at 180 °C-4h, over 200 °C degradation of the products in the liquid fraction starts to take place. Homogeneous basic and acid catalysts were used to improve the yields of the reaction. The kinetics of the hydrolysis of lignocellulosic structures to sugars were also analyzed and described, and reaction orders of 1 (LHW), 3 (HTC) and their respective reaction rate equations were reported.

The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective was to determine the flight pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study's lag; the lower the height, the greater the percentage of CBBs captured. In Experiments A and B, the traps placed at 0.5m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5m above the ground in the multi-level CT showed a higher capture percentage than the individually placed trap (also at 1.5m). The pattern of the capture and proportion of the CBB in the CTs were maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggested that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

In the former mining district of La Carolina (southern Spain), waste materials were accumulated without first waterproofing the substrate. Additionally, these mining dams were abandoned without any type of restoration, conditions that present a significant risk of contaminating the surrounding soils and waters. Prior to carry out the necessary works for isolating these residues, morphological characterization of the contact with the base substrate is needed. For that purpose, in recent years, different indirect study techniques have been used, among which electrical to-mography stands out. In this work, a less common geophysical technique, magnetometry, both in its magnetic and gra-diometric modalities, is used as an alternative method to analyse the geometry and structure of a mining dam. The results obtained with this methodology are compared with the results provided by electrical techniques, as well as with direct data from mechanical surveys and aerial photo-graphs prior to waste deposition. The magnetic anomaly curves obtained with geometric models generated with the Mag2dc program were also analysed. This comparative study shows the use-fulness of magnetic prospecting in characterizing the base geometry of these mining structures and therefore the interest in its application to environmental characterization studies.

Cancer is a disease that encompasses multiple and different malignant conditions and is among the leading causes of death in the world. Therefore, the search for new pharmacotherapeutic options and potential candidates that can be used as treatments or adjuvants to control this disease is urgent. Natural products, especially those obtained from plants, have played an important role as a source of specialized metabolites with recognized pharmacological properties against cancer, therefore, they are an excellent alternative to be used. The objective of this research was to evaluate the action of the monoterpene isoespintanol (ISO) against the human tumor cell lines MDA-MB-231, A549, DU145, A2780, A2780-cis and the non-tumor line MRC-5. Experiments with MTT and fluorescence with propidium iodide (PI), DAPI and green plasma revealed the cytotoxicity of ISO against these cells; furthermore, morphological and chromogenic studies revealed the action of ISO on cell morphology and the inhibitory capacity on reproductive viability to form colonies in MDA-MB-231 cells. Likewise, 3D experiments validated the damage in these cells caused by this monoterpene. These results serve as a basis for progress in studies of the mechanisms of action of these compounds and the development of derivatives or synthetic analogues with a better antitumor profile.

This work presents a novel compact CMOS potentiostat designed circuit for electrochemical cell. The proposed topology functions as a circuit interface, controlling the polarization of voltage signals at the sensor electrodes and facilitating current measurement during the oxidation-reduction process of a analyzed solution. The potentiostat, designed for CMOS technology, comprises a two-stage amplifier, two current mirror blocks coupled to this amplifier, and a CMOS push-pull output stage. It employs the electrochemical method of cyclic voltammetry, operating within voltage range of ±0.8 V and scan rates of 10mV/s, 25mV/s, 100mV/s and 250 mV/s. The circuit is capable of reading currents ranging from 10 µA to 500 µA. Experimental results were obtained using a potassium ferrocyanide (K3(FeCN)6) redox solution with concentrations of 10, 15 and 20 mmol/L, and their corresponding voltammograms were evaluated. The experimental results from a discrete circuit demonstrate that the proposed potentiostat topology produces outcomes consistent with those of classical topologies presented in the literature and industrial equipment.

Flexible energy storage devices, such as solid-state supercapacitors, are becoming increasingly attractive due to their characteristics of high electrochemical performance, reliability, light weight, flexibility, absence of electrolyte leakage, high power density, and long lifetime. For the optimization of the solid-state symmetrical supercapacitor proposed in this work, it was employed in sodium and lithium form Aquivion electrolyte membrane, which serves as the separator and electrolyte. As electrode materials, carbon xerogels, synthesized by microwave-assisted sol-gel methodology, with designed and controlled properties were obtained. Commercial activated carbon (YP-50F, 'Kuraray Europe' GmbH) was used for comparison. Specifically, the developed solid-state symmetrical supercapacitors deliver sufficient high specific capacitances of 105−110 F g−1 at 0.2 A g−1, along with an energy density of 4.5 Wh kg−1 at 300 W kg−1, and in a voltage window of 0-1.2 V in an aqueous environments, also demonstrating excellent cycling stability up to 10,000 charge/discharge cycles. These results can demonstrate the potential applications of carbon xerogel as an active electrode material and cation exchange membrane as the electrolyte in the development of solid-state supercapacitor devices

Efforts to optimize the design and enhance the efficiency of standing-wave thermoacoustic refrigerators (SWTAR), particularly those with parallel plate stacks, are crucial for achieving rapid and straightforward engineering estimates. This study primarily focuses on optimizing the Coefficient of Performance (COP) by combining the linear thermoacoustic theory (LTT) with the Design of Experiments (DOE) approach. The investigation centers around five key parameters affecting the COP, once the working gas is selected. Then, based on the LLT theory, the COP was estimated numerically, over defined intervals of those five parameters. Moreover, through quantitative and qualitative effect analyses, these five parameters and their interactions are determined. Utilizing a transfer function and surface response analyses based on the COP, the study aims to delineate the best COP value as well as the contribution of the thermoacoustic parameters and their interactions. Furthermore, a comparison between contour and surface responses and several statistical decision approaches applying the Full Factorial Design verify the robustness of the study’s findings. Ultimately, the COP results obtained align with existing literature, underscoring the validity and relevance of the study’s methodologies and conclusions.

The quest for youthful, healthy skin and full, vibrant hair has long been a driving force in the dermocosmetics field. However, traditional approaches often struggle to address the underlying causes of aging, damage, and hair loss. Regenerative cosmetics, powered by skin tissue engineering, offer a transformative alternative. This review explores the emerging field of using engineered skin tissues for cosmetic purposes, focusing specifically on their potential for anti-aging, repair, and hair restoration applications. We discuss how these technologies aim to rejuvenate aging skin by promoting collagen production, reducing wrinkles, and improving overall skin function. Additionally, the use of engineered skin for wound healing and scar reduction is examined, highlighting their potential to improve the appearance and functionality of damaged skin. Finally, we advance the exciting prospects of utilizing skin tissue engineering techniques to regenerate hair follicles, potentially offering solutions for hair loss and promoting denser hair growth.

UML (Unified Modeling Language) diagrams are graphical representations used in software engineering which play a vital role in the design and development of software systems and various engineering processes. Large, good-quality datasets containing UML diagrams are essential for different areas in the industry, research and teaching purposes, however few exist in the literature and it is common to find duplicate elements in the existing datasets. This might affect the evaluation of the models obtained when using these datasets. This paper addresses the challenge of creating a ground truth dastaset of UML diagrams, including semi-automated inspection to remove duplicates and ensure the correct labeling of all UML diagrams contained in the dataset. In particular, a dataset of six UML diagram classes has been assembled, comprising a total of 2,626 images (426 activity diagrams, 636 class diagrams, 352 component diagrams, 357 deployment diagrams, 435 sequence diagrams, and 420 use case diagrams). Importantly, unlike other existing datasets, ours contains no duplicate elements and all diagrams are correctly labeled. Our curated dataset is a valuable and unique resource for the research community because it serves as a foundation for training and evaluating various models. In this paper, we demonstrate this by training and testing several deep learning models using our dataset, achieving highly satisfactory results compared to those presented in other works in the literature. Additionally, our experimental results highlight the potential of Visual Transformers for UML diagram classification, setting our approach apart from others that predominantly used Convolutional Neural Networks for similar tasks.

In Mexico viticulture represents the second source of employment in the agricultural area after the fruit and vegetable sector. In developed countries, remote sensing is widely used for vineyard monitoring, however, this tool is barely used in developing countries of Iberoamerica. In this re-search, our overall objective is to characterize two vineyards in the state of Queretaro (Mexico) using Sentinel-2 and meteorological data, specifically spectral and thermal indices. Results showed that spectral indices obtained from Sentinel-2 bands have characterized adequately the phenolog-ical evolution of the different varieties of the vineyards. The Modified Soil-Adjusted Vegetation Index (MSAVI) was adequately used to discriminate the first stages of vineyards, while the Nor-malized Difference Vegetation Index (NDVI) was useful to monitor vineyards during the rest stages of vineyards. Thermal indices have shown that the best grape varieties were those that can adapt to both cooler and warmer temperatures, have a reasonable ripening period, and can produce wines with balanced acidity and flavors. In conclusion, the combination of meteorological (including thermal indices) and remote sensing data (NDVI and MSAVI) provide information for choosing the suitable grape variety for this region.

Artificial sweeteners are widely used food ingredients in beverages and drinks to lower calorie intake which in turn prevent lifestyle diseases such as obesity. Epidemiological evidences suggest that an overdose of artificial sweeteners could result to adverse effects after consumption. Thus, our study aims to systematically explore the potential adverse effects of eight commercial artificial sweeteners, including acesulfame-K, alitame, aspartame, sodium cyclamate, dulcin, neotame, saccharin and sucralose on cardiac performances of zebrafish (Danio rerio) and Daphnia as model animals. Embryonic zebrafish and Daphnia were exposed to eight artificial sweeteners at 100 ppb concentrations and their cardiac performance (heart rate, ejection fraction, fractional shortening, stroke volume, cardiac output and heartbeat regularity) were measured and compared. Saccharin significantly increased the heart rate of zebrafish larvae while a significant decrease was observed in Daphnia. Significant increase was also noted in zebrafish heart rate variability after incubation in acesulfame K, dulcin, sodium cyclamate, and sucralose. However, a significant increase in Daphnia was only observed after incubation in dulcin. Based on Principal Component Analysis (PCA) and hierarchical clustering results, several artificial sweetener samples were species-specific to zebrafish and Daphnia. Our study demonstrates the potential adverse physiological effects of artificial sweeteners in cardiovascular systems of zebrafish larvae and Daphnia.

The terahertz (THz) frequency range, often overlooked in the past, is now gaining recognition for its unique properties and diverse applications. THz waves, positioned between microwave and infrared frequencies, offer safety, broad bandwidth, and low energy consumption. This review highlights the burgeoning importance of THz technology in communication systems, spectroscopy, biomedical imaging, and various industries. It emphasizes the significance of novel antenna designs in enhancing THz system performance and functionality, enabling rapid communication, data transmission, spectroscopic analysis, and sensor capabilities.

Leishmaniasis are neglected diseases that affect regions such as South Asia, South Africa and Latin America, less developed regions. Current treatment, for cutaneous, mucocutaneous and visceral leishmaniosis, which are the main forms of the disease, is based on the administration of pentavalent antimonial and amphotericin B. However, these drugs have low efficacy and high toxicity. For this reason, the search for new treatments for this disease is necessary, based on studies of new molecules and their conformations. The research proposed the conformational study of brominated guanidine compounds with potential antileishmanial activity using Nuclear Magnetic Resonance (NMR) and X-ray diffraction (XRD) techniques. The present study involves the bro-minated molecules, LQOF-G2, LQOF-G30, LQOF-G35 and LQOF-G35-Br. The later was synthesized by the reaction of LQOF-G35 with NBS under IR irradiation at 120 Watts of potency and dichloro-methane as solvent by 12-h of exposition. The obtained results demonstrated the efficiency of the bromination method, since two bromines atoms entered the molecule. Furthermore, NMR analysis showed the occurrence of a conformational change from Z to E when compound LQOF-G35 was brominated to LQOF-G35-Br. This feature was well confirmed by comparative DRX study of the LQOF-G35 and LQOF-G35-Br compounds. The antileishmanial activity of LQOF-G2 e LQOF-G35 motivated the synthesis of new brominated compounds LQOF-G30 e LQOF-G35-Br.

Minimizing optical losses in resonant cavities is crucial for improving photonic device performance. This study focuses on the development of a simulation tool to analyze scattering losses in Fabry-Pérot interferometers (FPI), offering precise modeling of waveguide dynamics and contributing to accurate loss predictions across various platforms. Optical cavities often suffer from scattering losses due to surface roughness and material defects. Our approach integrates theoretical models and simulations to quantify these losses, utilizing the FPI as a model system. We identified upper and lower reflectivity thresholds, beyond which accurate measurement of losses becomes unreliable. For reflectivity below a certain threshold, measurement errors arise, while excessively high reflectivity can reduce fringe visibility and introduce detector sensitivity issues. Simulations were used to validate the model's ability to predict reflectivity and attenuation in waveguides with varying loss levels. The software’s flexibility to adjust transmission parameters for different cavity configurations enhances its utility for a broad range of photonic systems. Our study offers a novel methodology for optical loss analysis, with practical applications in optimizing photonic devices. By providing a reliable tool for precise loss measurement, this work supports advancements in optical technologies, enabling the design of more efficient, high-performance devices across various applications.

Taste disorders are common among cancer patients undergoing chemotherapy, with a prevalence ranging from 20% to 86%, persisting throughout treatment. This condition leads to reduced food consumption, increasing the risk of malnutrition. Malnutrition is associated not only with worse treatment efficacy and poor disease prognosis but also with reduced functional status and quality of life. The fruit of Synsepalum dulcificum (Daniell), commonly known as miracle berry or miracle fruit, contains miraculin, a taste-modifying protein with profound effects on taste perception. The CLINMIR Protocol is a triple-blind, randomized, placebo-controlled clinical trial designed to evaluate the regular consumption of a food supplement containing a miraculin-based novel food, dried miracle berry (DMB), on the taste perception (measured through electrogustometry) and nutritional status (evaluated through the GLIM Criteria) of malnourished cancer patients under active antineoplastic treatment. To this end, a pilot study was designed with 30 randomized patients divided into three study arms (150 mg DMB + 150 mg freeze-dried strawberries, 300 mg DMB or placebo) for three months. Throughout the five main visits, an exhaustive assessment of different affected parameters susceptible to improvement through regular consumption of the miraculin-based food supplement will be conducted, including electrical and chemical taste perception, smell perception, nutritional and morphofunctional assessment, diet, quality of life, fatty acid profile of erythrocytes, levels of inflammatory and cancer-associated cytokines, oxidative stress, antioxidant defense system, plasma metabolomics, and saliva and stool microbiota. The primary anticipated result is that malnourished cancer patients with taste distortion who consume the miraculin-based food supplement will report an improvement in food taste perception. This improvement translates into increased food intake, thereby ameliorating their nutritional status and mitigating associated risks. Additionally, the study aims to pinpoint the optimal dosage that provides maximal benefits. The protocol adheres to the SPIRIT 2013 Statement, which provides evidence-based recommendations and is widely endorsed as an international standard for trial protocols (https://www.spirit-statement.org/spirit-statement/). The clinical trial protocol has been registered at http://clinicaltrials.gov (NCT05486260).

Infections due to Candida spp., they are a threat to global health, with high rates of morbidity and mortality due to their drug resistance, especially in immunocompromised people. Thus, the search for new alternatives is urgent today. In recent years, combined therapy with compounds of natural origin has been proposed as an alternative. Considering the biological potential of isoespintanol (ISO) and continuing with its study, the objective of this research was to assess the effect of ISO in combination with the antifungals, fluconazole (FLZ), amphotericin B (AFB) and caspofungin (CASP), against clinical isolates of C. tropicalis and evaluate the cytotoxic effect of this compound in the acute phase (days 0 and 14) and chronic phase (days 0, 14, 28, 42, 56, 70 and 84), in female mice (Mus musculus) of the Balb/c lineage. The results show that ISO can potentiate the effect of FLZ, AFB and CASP, showing synergism with these antifungals. Evaluation of the mice by direct vision showed no behavioral changes or variation in weight during treatment; furthermore, the analysis of the cytokines IFN-γ and TNF in plasma, peritoneal cavity lavage (PCL) and bronchoalveolar lavage (BAL) indicated that there was no inflammation process and histopathological studies of lung, liver and kidney showed no signs of toxicity caused by ISO; this was consistent with the analysis of oxaloacetic transaminases (GOT) and pyruvic transaminases (GPT), which remained in the standard range. These findings indicate that ISO does not have a cytotoxic effect at the doses evaluated. Our results place ISO as a monoterpene of interest in the search for compounds with pharmacological potential.

A via ferrata (from the German “klettersteig”, hereinafter VF) is a sports route located on forest and mountains vertical rock walls equipped with steps, chains, artificial dams, bridges and other fixed elements and which have a steel cable (safety cable) all the way along allowing users to secure their progress and avoid possible falls [1]. This article aims to analyse the state of the art of the VF sector in Spain, especially in terms of the regulations of obligatory compliance, in addition to defining the basic characteristics of the installations to ensure that these are safe for users, providing a previously non-existent summary of the most important recommendations regardless of the country where they are installed.

Climate change has become a major concern for developing countries given the risk that it posses on energy and food independence, and on general productivity. Despite having an energy system with low carbon intensity when compared to other Latin American countries, Colombia is already facing climate change impacts and requires urgent efforts to mitigate them. As a developing country, the challenge is bigger as policies for economic growth should be in line with the global commitment of reducing greenhouse gas emissions. With the aim of contributing to the design of climate policies, this study assesses the impact of economic development on the environment by examining the validity of the Environmental Kuznets Curve hypothesis for Colombia. Statistically validated and stable autoregressive distributed lag models are estimated for three different environmental indicators: carbon dioxide emissions, methane emissions, and ecological footprint. Moreover, the effects of other variables such as urbanization, foreign direct investment, value added of agricultural and industrial sectors, and energy use are analyzed with dynamic simulations. Empirical evidence supports a long-run equilibrium relationship among investigated variables and the existence of an inverted U-shaped EKC relationship between Gross Domestic Product (GDP) and methane emissions, and GDP and ecological footprint. Shifting to renewable energy sources and leveraging the use of cleaner technologies in agricultural and industrial sectors are found to be key for economic growth without harming the environment.

We present a model of space that considers it to be a quantized dynamical entity which is a component of the universe along with matter and radiation. The theory is used together with thermodynamic data to provide a new view of cosmic evolution and an insight into the nature of dark energy and dark matter. Space is made up of energy quanta. The universe started from an atomic size volume at very high temperature and pressure near the Planck epoch. Upon expansion and cooling, phase transitions occurred resulting in the formation of radiation, fundamental particles, and matter. These nucleate and grow into stars, galaxies, and clusters. From a phase diagram of cosmic composition, we obtained a correlation between dark energy and the energy of space. Using the Friedmann equations, data from WMAP studies of the composition of the universe at 3.0 x 10⁵ (a=5.25 x 10^-2) years and at present (a=1), are well fitted by our model with an equation of state parameter, w= -0.7. The accelerated expansion of the universe, starting at about 7 billion years, determined by BOSS measurements, also correlates well with the dominance of dark energy at 7.25 x 10⁹ years ( a= 0.65). The expansion can be attributed to Quintessence with a space force arising from a quantum space field. From our phase diagram, we also find a correlation suggesting that dark matter is a plasma form of matter similar to that which existed during the photon epoch immediately prior to recombination. Our Quantum Space Model leads to a universe which is homogeneous and isotropic without the need for inflation. The thermodynamics of expansion is consistent with BOSS data that show the process to be adiabatic and the rate of expansion decelerating during the first 6 billion years after the Big Bang. However, it became non-adiabatic and accelerating thereafter. This implies an influx of energy from a source outside the universe; it warrants consideration as a possible factor in the accelerated expansion of the universe.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

Cyclodextrin (CD) is made up of 7 glucose molecules linked in a ring, creating a cone shape. Its interior can house hydrophobic molecules while the exterior is hydrophilic enough to interact with water molecules. Until now, this feature has been used for the development of active and intelligent packaging applied to food, interacting with the product or its environment to improve one or more aspects of its quality or safety. As well, it is used to provide information on monitoring the time in which food is optimal for consumption, an aspect considered very important for the consumer and for the merchant. A known problem with some of these types of packaging is that the bioactive compounds that are housed in the CD can interact with food and can modify its taste, smell, color and/or texture. Therefore, this review will focus on discerning which packaging is most appropriate for each situation.

We present a thermodynamic approach in modeling the evolution of the universe based on a theory that space consists of energy quanta, the spaceons. From wave-particle duality, they can be treated as an ideal gas. The model is similar to the Big Bang but without Inflation. It provides an insight into the nature of dark energy and dark matter, and an explanation for the accelerated expansion of the universe. The universe started from an atomic size volume of spaceons at very high temperature and pressure. Upon expansion and cooling, phase transitions occurred resulting in the formation of fundamental particles, and matter. These nucleate and grow into stars, galaxies, and clusters due to the action of gravity. From the cooling curve of the universe we constructed a thermodynamic phase diagram of cosmic composition, from which we obtained the correlation between dark energy and the energy of space. Using Friedmann’s equations, our model fits well the WMAP data on cosmic composition with an equation of state parameter, w= -0.7. The dominance of dark energy started at 7.25 x 10⁹ years, in good agreement with BOSS measurements. The expansion of space is attributed to a scalar quantum space field. Dark Matter is identified as a plasma form of matter similar to that which existed during the photon epoch, prior to recombination. The thermodynamics of expansion of the universe was adiabatic and decelerating during the first 7 billion years after the Big Bang; it accelerated thereafter. A negative pressure for Dark Energy is required to sustain the latter. This is consistent with the theory of General Relativity and the law of conservation of energy. We propose a mechanism for the acceleration as due to consolidation of matter forming Dark Energy Stars (DES) and other compact objects. The resulting reduction in gravitational potential energy feeds back energy for the expansion. Space will continue to expand and dark energy will undergo phase transition to a Bose-Einstein condensate, a superfluid form of matter. Self-gravitation can cause a bounce and start a new Big Bang. We show how the interplay of gravitational and space forces leads to a cyclic, maybe eternal, universe.

When we attempt to define life, we tend to refer to individuals, those that are alive. But these individuals might be cells, organisms, colonies... ecosystems? We can describe living systems at different scales. Which ones might be the best ones to describe different selves? I explore this question using concepts from information theory, ALife, and Buddhist philosophy. After brief introductions, I review the implications of changing the scale of observation, and how this affects our understanding of selves at different structural, temporal, and informational scales. The conclusion is that there is no single ``best'' scale for a self, as this will depend on the scale at which decisions must be made. Different decisions, different scales.

Information theory has been developed for seventy years with technological applications that have transformed our societies. The increasing ability to store, transmit, and process information is having a revolutionary impact in most disciplines. The goal of this work is to compare the formal approach to information with Buddhist philosophy. Considering both approaches as compatible and complementary, I argue that information theory can improve our understanding of Buddhist philosophy and vice versa. The resulting synthesis leads to a worldview based on information that overcomes limitations of the currently dominating physics-based worldview.

In the present work, we evaluate the prediction capability of six Pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (Ks). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were construct for Ks from clay percentage, bulk density and saturation water content data. The results show, for the evaluated models, that one model present an overestimation for Ks>0.5 cm h-1 values, three models have a underestimation for Ks>1.0 cm h-1 and two models have a good correlation (R2>0.98) but are necessary more than three parameters. Nevertheless, the last two models requires from three to four parameters in order to get the optimization. By other hand, the models proposed in this work have a similar correlation with a less number of parameters: the fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and a R2 = 0.9901 when we use two.

The scientific fields of complexity, artificial life (ALife), and artificial intelligence (A.I.) share commonalities: historic, conceptual, methodological, and philosophical. Although their origins trace back to the 1940s birth of cybernetics, they were only able to properly develop as modern information technology became available. In this perspective, I offer a personal (and thus biased) account of the expectations and limitations of these fields, some of which have their roots in the limits of formal systems. I will use interactions, self-organization, emergence, and balance to compare different aspects of complexity, ALife, and A.I. Even when the trajectory of the paper is influenced by my personal experience, the general questions posed (which outweigh the answers) hopefully will be useful to align efforts in these fields toward overcoming --- or accepting --- their limits.

Myotoxic phospholipases A₂ are responsible for many clinical signs in envenomation by Bothropssnakes. A new myotoxic acidic PLA₂ Asp 49 was isolated from Colombian Bothrops asper venom. It was isolated by high efficiency liquid chromatography and named BaCol PLA₂. It had a molecular weight of 14180.69 Da and an isoelectric point of 4.4. The complete sequenceobtained by cDNA cloning, with access number in the gene bank MF319968; this sequenceevidenced a mature product of 124 amino acids with Asp in 49 position. In vivoassaysin mice demonstrated profuse oedemaand myotoxicity evidenced by increase of creatinakinasa in plasma and severe and diffuse damage to the muscular fibers, further vacuolization and hyalinization necrosis of the sarcoplasm showed by histopathology with hematoxylin and eosin staining of gastrocnemius muscle. In vitro studies showed cell membrane damage without phosphatidylserine exposure, an early apoptosis hallmark. Further BaCol PLA₂ evidenced high indirect hemolytic activityand moderate anticoagulant action. The toxin showed homology with others acidic PLA₂ isolated from Bothrops venoms, including one isolated from B. asper of Costa Rica. Unlike this, BaCol PLA₂ was myotoxic.

I present a personal account of self-organizing systems. As such, it is necessarily biased and partial. Nevertheless, it should be useful to motivate useful discussions. The relevant contribution is not my attempts at answering questions (maybe all my answers are wrong), but the steps towards framing relevant questions to better understand self-organization, information, complexity, and emergence. With this aim, I start with a notion and examples of self-organizing systems (what?), continue with their properties and related concepts (how?), and close with applications (why?).

This article discusses collaborative ethnography as a meaningful source for spatial research, in particular, for participatory methodologies in urban planning and placemaking processes. It investigates the experiences with co-creation and co-research in different research projects to gain insight into the performance of collaborative ethnography as a technique to explore and enrich local knowledge. To better understand the possible causal relationships between the experience gained in the projects and the learnt lessons, we also identify recommendations for improving research methodologies to be applied in placemaking. The article concludes that collaborative ethnography is an effective tool for adding value to spatial co-research and co-creation processes. It opens opportunities for the co-production of space, ideas and knowledge, contributing at the same time to better informed decision-making. It also helps improve ideas and gather insights into the spatial needs of focus groups.

Background: In recent years, the integration of robotic systems into various aspects of daily life has become increasingly common. As these technologies continue to advance, ensuring user-friendly interfaces and seamless interactions becomes more essential. For social robots to genuinely provide lasting value to humans, a favourable user experience (UX) emerges as an essential prerequisite. Aim: This article aimed to evaluate the usability of the MINI robot, highlighting its strengths and areas for improvement based on user feedback and performance. Method: In a controlled lab setting, a mixed-method qualitative study was conducted with ten individuals aged 65 and above diagnosed with mild dementia (MD) and mild cognitive impairment (MCI). Participants engaged in individual MINI robot interaction sessions, completing cognitive tasks as per written instructions. Video and audio recordings documented interactions, while post-session System Usability Scale (SUS) questionnaires quantified usability perception. Ethical guidelines were followed, ensuring informed consent, and the data underwent qualitative and quantitative analyses, contributing insights into the MINI robot's usability for this demographic. Results: The study addresses the ongoing challenges that tasks present, especially for MD individuals, emphasizing the importance of user support. Most tasks require both verbal and physical interactions, indicating that MD individuals face challenges when switching response methods within subtasks. These complexities originate from the selection and use of response methods, including difficulties with voice recognition, tablet touch, and tactile sensors. These challenges persist across tasks, with individuals with MD struggling to comprehend task instructions and provide correct answers and individuals with MCI struggling to use response devices, often due to the limitations of the robot's speech recognition. Technical shortcomings have been identified. The results of the System Usability Scale (SUS) indicate positive perceptions, although there are lower ratings for instructor assistance and pre-use learning. The average SUS score of 68.3 places device usability in the "good" category. Conclusion: Our study examines the usability of the MINI robot, revealing strengths in quick learning, simple system and operation, and integration of features while also highlighting areas for improvement. Careful design and modifications are essential for meaningful engagement with people with dementia. The robot could better benefit people with MD and MCI if clear, detailed instructions and instructor assistance are available.

The study aims to explain the different effects between the multiplication, addition, division and subtraction equations. In this sense, multiplication and addition equations develop a new element or fact, meanwhile, division equations express information within the element or fact, subtraction is the selection of element or fact. Furthermore, for a multiplication and addition equation results in the new element or fact, it is necessary to depend on specific physical concepts, without extreme alteration, as it would result in the alteration of the element or fact. It is worth highlighting the importance of fixed values ​​in the equation to describe the specific nature of the element or fact. The study makes it possible to understand open equations (without solutions) in mathematics and physics, in addition to understanding existing equations. The study makes reference to the theory of obligatory necessity and the theory of differences between elements.

We present a Quantum Space Model (QSM) of the evolution of the universe based on the theory that space consists of energy quanta from which it began. We used the Friedmann equations to trace its history and show that Dark Energy is the energy of space which caused its accelerating expansion.The universe started from a quanta of space which was triggered by quantum fluctuations that caused the Big Bang. It then expanded and cooled undergoing phase transitions to radiation, fundamental particles, and matter. Matter grew into galaxies, and was consolidated by gravity into Black Holes, ending in a Big Crunch and Deep Freeze inside a Black hole at 1.380 trillion years. Fluctuations caused a new Bang to start another cycle in its life. If the Law of Conservation of Energy is universal, then the cosmos is eternal. Our results support the theoretical predictions of a cyclic universe by Steinhardt and associates, as well as Penrose. Space and energy are equivalent as embodied in the Planck energy equation. They are the two most fundamental quantities that govern cosmic evolution. The two principal long range forces are the gravitational force and the space force,which maybe the fifth force in the universe. They provide the clockwork mechanism operating our cyclic universe.

The COVID-19 pandemic has led to the growth of hybrid and online learning environments and the trend to introduce more technology into the classroom. One such change would be the use of smart synchronous hybrid learning environments (SSHLE), which are settings with both in-person and online students concurrently, and in which technology plays a key role in sensing, analyzing, and reacting throughout the teaching and learning process. These changing environments and the incorporation of new technologies can place a greater orchestration load on participants and a reduction in teacher agency. In this context, the aim of this paper is to analyse the orchestration load and teacher agency in different SSHLEs. The NASA-TLX model was used to measure the orchestration load in several scenarios. Questionnaires and interviews were used to measure teacher agency. The results obtained indicate that the orchestration load of the teacher tends to be high (between 60 and 70 points out of 100 of the NASA-TLX workload), especially when they lack experience in synchronous hybrid learning environments, and the orchestration load of the students tends to have average values (between 50 and 60) in the SSHLEs analysed. Meanwhile, the teacher agency does not appear to be altered but shows potential for improvement.

This paper presents a comprehensive analytical-numerical algorithm constructed for proprotor performance evaluation, focusing on accommodating large inflow angles. The algorithm’s design, range, and analytical features are clarified, indicating its potential to improve performance analysis, particularly for blades with substantial pitch variations. The Stahlhut model has not been validated against the conventional BEMT small-inflow angle methodology. This paper implements a modified Stahlhut model, coupled with the conventional BEMT theory. Preliminary validations of the model demonstrate promising results, with deviations reduced to -3% to 4% compared to conventional BEMT methods exhibiting deviations as high as 20% to 88% against experimental data for a highly twisted proprotor. The reconsideration of the computational module carries considerable implications for the design and refinement of proprotors, providing alternative analysis methods that could improve operational effectiveness across a range of flight scenarios. Drawing upon the theoretical framework presented by Stahlhut, the algorithm enables a more complex understanding of proprotor dynamics, facilitating accurate predictions of the loads at each blade section. The introduced algorithm emerges as a valuable asset for evaluating proprotor performance during the early stages of design and certification, offering both low computational cost and medium to high reliability.

Data collected at the Cascais tide gauge, located on the west coast of Portugal Mainland, have been analyzed and sea level rise rates have been updated. Based on a bootstrapping linear regression model and on polynomial adjustments, time series are used to calculate different empirical projections for the 21^st century sea level rise, by estimating the initial velocity and its corresponding acceleration. The results are consistent to an accelerated sea level rise, showing evidence of a faster rise than previous century estimates. Based on different numerical methods of second order polynomial fitting, it is possible to build a set of projection models of relative sea level rise. Appling the same methods to regional sea level anomaly from satellite altimetry, additional projections are also built with good consistency. Both data sets, tide gauge and satellite altimetry data, enabled the development of an ensemble of projection models. The relative sea level rise projections are crucial for national coastal planning and management since extreme sea level scenarios can potentially cause erosion and flooding. Based on absolute vertical velocities obtained by integrating global sea level models, neo-tectonic studies and permanent Global Positioning System (GPS) station time series, it is possible to transform relative into absolute sea level rise scenarios, and vice-versa, allowing the generation of absolute sea level rise projection curves and its comparison with already established global projections. The sea level rise observed at the Cascais tide gauge has always shown a significant correlation with global sea level rise observations, evidencing relatively low rates of composed vertical land velocity from tectonic and post-glacial isostatic adjustment, and residual synoptic regional dynamic effects rather than a trend. An ensemble of sea level projection models for the 21st century is proposed with its corresponding probability density function, both for relative and absolute sea level rise for the west coast of Portugal Mainland.

O estudo apresenta uma afirmação e explicação de que ocorrem progressões numéricas maiores e menores que dependem da representação contida no espaço físico. Em casos gerais, números maiores são múltiplos e números menores são simples, porque vários números contêm mais números em muitos espaços físicos do que números simples. Em casos específicos, dependem da afirmação do que é a representação específica, podendo ocorrer realidades diferentes de casos gerais. Além disso, a teoria explica a mudança no número de números primos.

Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). Current solutions for its management, such as oral rehydration salts (ORS), inhibitors of the gut motility, antibiotics, and living probiotics only partially counteract the mechanisms of the disease and do not provide a full coverage of the problem. Potential risks of the use of living probiotic strains, particularly in immunocompromised patients, can be eliminated with the use of tyndallized (heat-killed) postbiotic bacteria and yeast. ABB C22® is a postbiotic combination of three tyndallized yeasts, namely Saccharomyces boulardii, Saccharomyces cerevisiae, and Kluyveromyces marxianus. To assess the action of the postbiotic combination on diarrhoea, immune and gut epithelial cell signaling assays, gut barrier formation assay and rotavirus gene expression assay were performed. ABB C22® showed a strong anti-inflammatory effect, an induction of the build-up of the gut epithelium, and a degree of protection against rotavirus infection. These experimental studies support the use of the postbiotic ABB C22® as a solution for the management of diarrhoea and gastrointestinal conditions, alone or in combination with existing but incomplete treatments.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

Will human societies accommodate social robots, given the current development rate? Are we under a novelty effect? Can (and should) social robots compete with intelligent agents (e.g., software robots) for the attention of humans? Will the current development of machine learning be the motor of social robotics? What kind of robotics products and culture can we expect that will emerge? These are relevant questions to assess the sustainability of social robots and how they will change business practices and lifestyle. Speculative/exploratory arguments on these topics are possible and have been mostly left out of research papers. This, however, results in an unconventional structure where the novelty comes from the questioning of the role of Social Robotics that has not been duly addressed in the literature. The paper raises questions and (i) presents arguments supporting sustainability grounded on experiments in real-world scenarios, and (ii) identifies challenges according to multiple viewpoints. These are questions for which assertive answers are not found in the literature. Besides the answers to the above questions, the conclusions point to pathways we believe social robotics can evolve, e.g., incorporating maximal knowledge on how humans work.

Mathematical optimization offers a valuable approach to tackle Industry scheduling problems. By formulating the scheduling challenge as a mathematical problem, mathematical optimization enables efficient and effective decision-making processes. Mathematical optimization is particularly beneficial in complex scheduling scenarios, such as in networked manufacturing environments, where multiple jobs and resources need to be coordinated. By leveraging optimization models and algorithms, it becomes possible to generate optimal process plans, considering factors like job dependencies, resource availability, and timing constraints. Through mathematical optimization, organizations can achieve improved efficiency, reduced lead times, and enhanced utilization of resources. Rigorous mathematical formulations and optimization techniques enables to surpass traditional manual planning methods and brings forth powerful computational capabilities. By optimizing various scheduling objectives, from minimizing makespan to maximizing resource utilization, mathematical optimization provides organizations with valuable insights and actionable plans. The purpose of this study is to discuss scheduling solutions for multiple jobs in a networked manufacturing setting based on mathematical optimization process. The study analyses a solver-based approach to generate the optimal process plans for multiple jobs and compare it with a more traditional game-theoretic approach. The objectives aim to develop two solver-based model using Z3 and Gurobi to generate optimal process plans; implement a game-theoretic model to solve for the same set of scheduling problems, and compare the computational time, solution quality, and efficiency of both approaches. To achieve this, the methodology will start with the problem definition. Multiple jobs are to be scheduled on a set of parallel machines. Each job has predefined processing times, deadlines, and priorities. The objective is to minimize the total completion time and maximize machine utilization while meeting all deadlines.

The theory says that the first things to exist in the universe and the current moment were driven by an imperative need; that is, the intensities of the physical concept specify influence the existence of elements and facts based on the countless observations in physical spaces in relation to elements and facts. The existence of mandatory elements in space is motivated by the characteristics of the spaces that offer conditions for such an obligation. The theory states that the universe did not arise by chance; that is, the universe emerged through determination influenced by its surroundings. The objective of the study is to help explain the elements and facts of the universe from its origins to the present.

(1) Objectives. Patients with heart failure (HF) who experience hospitalizations for worsening HF (HFH) are at high risk of subsequent events. We aimed to evaluate the impact of an outpatient care management program that includes a clinician-to-clinician e-consultation using an integrated electronic medical record in a healthcare area with a widely dispersed population on delay time in care, hospital admissions, and mortality in a high-risk group of patients with HF and previous episodes of HFH. (2) Methods. We selected 6,444 HF patients who visited the cardiology service at least once between 2010 and 2021. Of these, 4,851 were attended in e-consult, and 2,008 in one-time in-person consultations. In 2,230 HF patients, there was documentation of a previous episode of HFH. Using an interrupted time series regression model, we analysed the impact of incorporating e-consult into the health care model in the group of patients with HFH and evaluated the elapsed time to cardiology care, heart failure (HF), cardiovascular (CV), and all-cause hospital admissions and mortality, calculating the incidence relative risk (iRR). (3) Results. In the group of patients with previous HF hospitalizations, the introduction of e-consult substantially decreased waiting times to cardiology care. The time elapsed to care after e-consult implementation was significantly reduced compared with the previous in-person period (8.6 [8.7] vs 55.4 [79.9] days, p&lt;0.001). In that group of patients, after e-consult implantation, hospital admissions for HF were reduced (iRR [CI95%]: 0,837 [0,840-0,833]), 0,900 [0,862-0,949] for CV and 0,699 [0,678-0,726] for all-cause hospitalizations. There was also lower mortality (iRR [CI95%]: 0.715 [0.657-0.798] due to HF, 0,737 [0.764-0.706] for CV and 0,687 [0.652-0,718] for all-cause). The improved outcomes after e-consultation implementation were significantly higher in the group of patients with previous HFH and were independent of the patient’s clinical characteristics managed during the in-person or e-consultation periods. (4) Conclusions. In HF patients with previous HFH, an outpatient care program that includes an e-consult significantly reduced waiting times to cardiology care and was safe, with a lower rate of hospital admissions and mortality in the first year.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

In recent years, music education in Ibero-America has been losing ground within the school environment in favor of the development of curricular systems that benefit academic results in standardized tests. Despite this, several studies in the field of cognitive neurosciences have found evidence of great relevance and in which it can be observed how music education can favor cognitive development and performance in practically all stages of human development, with important results in language tasks, attention, and executive functions such as planning, inhibition, cognitive flexibility and working memory.

This paper presents a hybrid probability distribution known as the FCD, which is based on the hazard functions of the Fréchet and Chen distributions. A notable characteristic of the FCD is its ability to model monotonic (increasing and decreasing) and non-monotonic (bathtub-shaped) behaviors, commonly linked to electrical and electronic device failure times in reliability analysis. The paper explores the statistical properties relevant to the reliability analysis of these devices. It proposes a Maximum Likelihood Estimator (MLE) and Bayesian Analysis equations for estimating the parameters of the FCD. Three case studies of electronic device lifetimes with varying behaviors were analyzed to validate the proposed methodology. The FCD was compared to other distributions with similar characteristics, and the results from each case study demonstrated that the proposed distribution yields competitive outcomes, closely reflecting the behavior of the devices analyzed, making it a valuable option for reliability engineering practitioners in warranty and maintenance time evaluations

Neurodegenerative diseases encompass a broad spectrum of profoundly disabling disorders that impact millions of individuals globally. While their underlying causes and pathophysiol-ogy display considerable diversity and remain incompletely understood, a mounting body of evidence indicates that the disruption of blood-brain barrier (BBB) permeability, resulting in brain damage and neuroinflammation, constitutes a shared characteristic among them. Con-sequently, targeting the BBB has emerged as an innovative therapeutic strategy for address-ing neurological diseases. Within this review, we not only explore the neuroprotective, neu-rotrophic, and immunomodulatory benefits of mesenchymal stem cells (MSCs) in combating neurodegeneration but also delve into their recent role in modulating the BBB. We will delve into the cellular and molecular mechanisms through which MSC treatment impacts primary age-related neurological disorders like Alzheimer’s disease, Parkinson’s disease, and stroke as well as immune-mediated conditions such as multiple sclerosis. Our focus will center on how MSCs participate in the modulation of cell transporters, matrix remodeling, stabilization of cell-junction components, and restoration of BBB network integrity in these pathological con-texts.

Circulating tumor cells (CTC) have shown to be prognostic in advanced colorectal cancer (advCRC), but their value for predicting response to treatment or as a source of molecular data is debated. We compared CellSearch® (Janssen Diagnostics, LLC) and IsoFlux^TM (Fluxion Biosciences Inc, South San Francisco, CA) systems for the enumeration of CTC in patients with newly diagnosed advCRC (group 1; n=34). Using castPCR^TM we studied KRAS status in CTC isolated with IsoFlux^TM and compared it with that of the primary tumor in patients from group 1 and in KRAS wild-type (KRAS^WT) patients with progressive disease (group 2; n=22). Median number of CTC detected with CellSearch® (groups 1 and 2) was 1 (range: 0-78) and with IsoFlux^TM (group 1) was 8 (range: 0-419), showing a modest correlation (r=0.345, P=0.036), which improved if lung metastases (r=0.805, P=0.016) or if lung and liver metastases were present (r=0.812, P=0.05). A Bland-Altman plot showed that the higher the number of CTC detected the larger the difference between both methods in favor of IsoFlux^TM. After a median follow-up since CTC collection of 16 months (range: 1-30) CellSearch® ≥ 3 CTC (HR 2.77, 95% CI 0.77-9.95) and IsoFlux^TM ≥ 11 CTC (HR 4.14, 95% CI 1.05-16.19) were established as the best cutoff points for predicting survival. Using castPCR^TM we found KRAS mutations in CTC in 4 out of 8 patients from group 1 and in 2 out of 3 patients from group 2. None of these mutations were found in the primary tumor using standard methods, possibly reflecting intratumor heterogeneity or treatment selection pressure. We conclude that IsoFlux^TM is more efficient than CellSearch® in the isolation of CTC in patients with advCRC, achieving, in a majority of cases, the established minimum of CTC for castPCR^TM-based genetic analyses.

ABSTRACT: Psychological vulnerability (PV) and low mental health literacy correlate negatively with higher education students' positive mental health and health behaviours. Levels of mental health literacy limit self-help, adaptative coping strategies and academic success. However, few studies examine the significant differences between students' PV, mental health literacy, positive mental health (PMH) and modifiable behaviours variables. Identifying modifiable vulnerability factors is essential when seeking and providing professional help. Method: A cross-sectional descriptive study was conducted to investigate the differences between modifiable behaviours and PV, mental health literacy, and PMH in higher education students. A sample of 3,600 undergraduate students was recruited, mostly female (78.8%), with an average age of 23 years (SD = 6.68). Results: The majority were women, did not exercise, were dissatisfied with sleep quality time per night (62.1% sleep less than 7 hours per night) and did not engage in leisure activities. Also, most respondents had PV and low literacy levels, particularly at F1, and 67.9% scored in the flourishing group. Results showed significant differences (p<0.001) between gender, age, sleep, exercise, diet, leisure activities and PV, and PMH and literacy. Conclusions: The results identified modifiable vulnerability factors that underpin the design of intervention-targeted programmes to promote literacy and PMH in higher education campuses in Portugal to foster students’ well-being and self-help strategies.

In this working paper we intended to address the emergence of what, potentially, will be a central concept in the very near future, Society 5.0 and that arises politically in (with) following the implementation of the concept of Industry 4.0. Society 5.0 proposes to deepen the potential of the individual-technology relationship in the promotion of the improvement of the quality of life of all people through a super smart society, is an extremely recent concept as a guiding social development that can have a profound impact in societies at all levels, such as quality of life and sustainability. It is a presentation that is based on very recent3 publications, but which also has a prospective component, which always generates some indetermination and uncertainty. Also, for this reason, it is a contribution that seeks above all else to contribute to this very urgent and necessary discussion.

This article aims to understand the domains and conceptual uses of contagion, its modalities and its effects, in its different historical contexts and meanings, as an expression of the process of interdependence between the positions and the different points of view of different actors involved in multiple scientific, moral, social and political challenges. Another objective focuses on understanding the process of collective management of contagion, disease and health, where prevention is an essential element of its objectives and justifications, its discursive order, as well as its practical activities.

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.

Groundwater pollution in intensive horticultural areas is becoming an increasingly important problem. Therefore, this study evaluates nitrogen (N) fertilization in open field processing pepper crop in Extremadura, Spain. Previous research on the effect of N on sweet peppers grown in greenhouses is abundant, but data on outdoor cultivation, especially considering variety and site influences, are lacking. Field trials were conducted in 2020, 2021 and 2022 to determine the opti-mum N fertilizer rate for processing peppers, with the aim of reducing environmental impacts such as nitrate leaching while maintaining crop yields. Different N rates were applied in the trials, ranging from no N fertilizer to 300 kg N/ha. Meas-urements included crop yield, biomass, intercepted photosynthetically active radiation (PAR), and canopy cover. The study also developed a critical nitrogen curve (CNC) to determine the minimum N concentration required for optimal growth. The results showed that applying more than 200 kg N/ha did not significantly increase yield. Nitrogen-free treatments resulted in earlier fruit maturity, concentrating the harvest and reducing waste. In addition, excessive N application led to envi-ronmental problems such as groundwater contamination due to nitrate leaching. The study concludes that outdoor pepper crops in this region can achieve optimal yields with lower N rates (around 120 kg N/ha) compared to current practices, thereby reducing environmental risks and fertilizer costs. It also established relationships between biomass, canopy cover, and N uptake to improve fertilization strategies. These data support future crop modelling and sustainable fertili-zation practices.

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.

Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). Current solutions for its management, such as oral rehydration salts (ORS), inhibitors of the gut motility, antibiotics, and living probiotics only partially counteract the mechanisms of the disease and do not provide a full coverage of the problem. Potential risks of the use of living probiotic strains, particularly in immunocompromised patients, can be eliminated with the use of tyndallized (heat-killed) postbiotic bacteria and yeast. ABB C22® is a postbiotic combination of three tyndallized yeasts, namely Saccharomyces boulardii, Saccharomyces cerevisiae, and Kluyveromyces marxianus. To assess the action of the postbiotic combination on diarrhoea, immune and gut epithelial cell signaling assays, gut barrier formation assay and rotavirus gene expression assay were performed. ABB C22® showed a strong anti-inflammatory effect, an induction of the build-up of the gut epithelium, and a degree of protection against rotavirus infection. These experimental studies support the use of the postbiotic ABB C22® as a solution for the management of diarrhoea and gastrointestinal conditions, alone or in combination with existing but incomplete treatments.

Sociology and History as consolidated scientific and academic projects have maintained a peculiar and paradoxical relationship. The growing disciplinary and subdisciplinary specialization of these two sciences poses relevant epistemological and methodological challenges to face potential situations of isolation, fragmentation and enable the apology of an interdisciplinary perspective characterized by the historicity of social structures, actions and senses.Several types of reasons shape this diffuse process of approach/distinction between Sociology and History, namely, epistemological and methodological, disciplinary closure, academic, professional, configuring what can be called contained dialogues. This paper, starting from the sociological perspective of the authors, seeks to contribute to the reflection on the relevance of a scientific project aimed at affirming an interdisciplinary perspective that may foster the heuristic potentialities of both Sociology and History in the analysis of the complexity of social reality and human action.

The Theory of differences between elements explains the reasons for the differences in physical concepts between different elements, such as quantum physics and the Theory of general relativity, being explained through observations. Thus, it is possible to conclude from the observations that the differences are motivated by the reactions between the elements, by the composition of the elements, and by the influence of the spaces that promote losses and gains of characteristics; therefore, there is no general similarity between quantum physics and the general Theory of relativity. The study aims to understand the elements and their physical concepts that make up the Universe.

Study of alterations in Osteoarthritis (OA) of Glypicans 1 to 6 (GPCs) and Notum in plasma, bone marrow mesenchymal stromal cells (BM-MSCs) and osteoblasts. Plasma levels of GPCs and Notum were measured of 25 patients and 24 healthy subjects. In addition, BM-MSCs from eight OA patients and eight healthy donors were cultured during 21 days with culture me-dium and osteogenic medium. Protein and gene expression levels of GPCs and Notum were de-termined by ELISA and qPCR at 0, 7 ,14 and 21 days. GPC5 and Notum have been found de-creased in OA patients’ plasma. OA BM-MSCs showed downexpression of GPC6 and upregula-tion of Notum. A decrease in GPC5 and Notum proteins and an increase in GPC3 were found. During osteogenic differentiation, elevated GPC2, 4, 5, 6 and Notum mRNA levels and decreased GPC3 were observed in OA. Furthermore, the protein levels of GPC2, GPC5 and Notum de-creased and GPC3 increased. Glypicans and Notum are altered in BM-MSCs and during osteo-genic differentiation from patients with OA. Furthermore, GPC5 and Notum can be proposed as new biomarkers of the pathology. The alterations found indicate that Notum could be a prom-ising therapeutic strategy for Osteoarthritis.

Aedes (Stegomyia) albopictus is a mosquito native to Southeast Asia. Currently, it has a wide distribution in America where natural infection with arboviruses of medical and veterinary importance has been reported. In spite of their importance in the transmission of endemic arbovirus, basic information of parameters affecting their vectorial capacity is poorly investigated. The aim of the work was to update the distribution range of Ae. albopictus in the Americas, review the blood-feeding patterns and compare the minimum infection rate (MIR) of the dengue virus (DENV) between studies of vertical and horizontal transmission. The current distribution of Ae. albopictus encompasses 21 countries in the Americas. Extensive review has been conducted for the blood-feeding patterns of Ae. albopictus. The results suggest that the mosquito is capable of feeding on 16 species of mammals and five species of avian. Humans, dogs, and rats are the most common host. Eight arboviruses with the potential to infect humans and animals have been isolated in Ae. albopictus. In the United States of America (USA), Eastern equine encephalitis virus, Keystone virus, La Crosse Virus, West Nile virus, and Cache Valley virus were isolated in the Asian mosquito. In Brazil, Mexico, Colombia, and Costa Rica, DENV (all serotypes) has been frequently identified in field-caught Ae. albopictus. Overall, the estimated MIR in Ae. albopictus infected with DENV is similar between horizontal (10.95) and vertical transmission (8.28). However, in vertical transmission, there is a difference in the MIR values if the DENV is identified from larvae or adults (males and females emerged from a collection of eggs or larvae). MIR estimated from larvae is 14.04 and in adults is 4.04. In conclusion, it has to be highlighted that Ae. albopictus is an invasive mosquito with wide phenotypic plasticity to adapt to broad and new areas, it is highly efficient to transmit the DENV horizontally and vertically, it can participate in the inter-endemic transmission of the dengue disease, and it can spread zoonotic arboviruses across forest and urban settings.

The aim of the work was to update the distribution range of Aedes (Stegomyia) albopictus Skuse in the Americas, review the blood-feeding patterns and compare the minimum infection rate (MIR) of the dengue virus (DENV) between studies of vertical and horizontal transmission. The current dis-tribution of Ae. albopictus encompasses 21 countries in the Americas. Extensive review has been conducted for the blood-feeding patterns of Ae. albopictus. The results suggest that the mosquito is capable of feeding on 16 species of mammals and five species of avian. Humans, dogs, and rats are the most common host. Eight arboviruses with the potential to infect humans and animals have been isolated in Ae. albopictus. In the United States of America (USA), Eastern equine encephalitis virus, Keystone virus, La Crosse Virus, West Nile virus, and Cache Valley virus were isolated in the Asian mosquito. In Brazil, Mexico, Colombia, and Costa Rica, DENV (all serotypes) has been frequently identified in field-caught Ae. albopictus. Overall, the estimated MIR in Ae. albopictus infected with DENV is similar between horizontal (10.95) and vertical transmission (8.28). However, in vertical transmission, there is a difference in the MIR values if the DENV is identified from larvae or adults (males and females emerged from a collection of eggs or larvae). MIR es-timated from larvae is 14.04 and in adults is 4.04. In conclusion, it has to be highlighted that Ae. albopictus is an invasive mosquito with wide phenotypic plasticity to adapt to broad and new areas, it is highly efficient to transmit the DENV horizontally and vertically, it can participate in the inter-endemic transmission of the dengue disease, and it can spread zoonotic arboviruses across forest and urban settings.

The Autopoiesis and Cognition Theory (ACT), by Maturana and Varela, based on the notions of Biological Closure and Structural Coupling, is a well-known theory on how to understand biological organization [1, 2, 3]. Although, for example, the Free Energy Principle framework evokes some entailments of autopoiesis in a more formal setting [4, 5]; and ACT has been used in many fields, its impact has been restricted because it lacks quantitative analysis. Here we present a theoretical framework grounded in accepted and well-developed ideas from Mathematics and Physics which advance the understanding of the Principles of Biological Organization under the guidance of Biological Closure and Structural Coupling. The disciplines of Differential Geometry/Topology, Mechanics and Complex Dynamical Systems provide a powerful, elegant, and well-established body of knowledge to support our Biological Organization Principles (BOP) framework. In particular, Stochastic Mechanics and KAM theory (from Kolmogorov, Arnold and Moser theorem) allow us to develop, using the notions of Biological Closure and Structural Coupling, a central core of BOP termed Dynamical Closure Mechanism. Under the proposed framework, a wide variety of bio- logical phenomena can be understood, shedding new light on biological explanations. However, an understanding of biological organization may require the re-evaluation of dogmas on how we think on biology as it seems inescapable that what is needed is an integration of analysis and notions derived from mathematics, physics, and biology to generate a new landscape of ideas.