We sought to evaluate the effects of non-surgical periodontal treatment (NSPT) on periodontal clinical parameters, systemic blood pressure (BP) and plasma levels of systemic inflammation markers in patients with combined refractory arterial hypertension (RAH) and stage III grade B periodontitis. Twenty-seven participants with RAH and periodontitis received NSPT. The analyzed clinical parameters were probing depth (PD), clinical attachment level (CAL), bleeding on probing (BOP), and plaque index (PI). An assessment was performed for systemic BP, complete blood count, coagulogram, creatinine measurement, C-reactive protein (CRP), glycated hemoglobin, cholesterol, glutamic oxaloacetic transaminase, glutamate pyruvic transaminase, waist-hip ratio, and body mass index. In the follow-up period, twenty-two patients were evaluated at baseline and after 90 and 180 days. The data were submitted to statistical analysis (α=0.05%). As expected, the clinical results showed a significant improvement in the percentages of PI, BOP, PD and CAL, which were statistically significant at 90 and 180 days (p<0.0001). Importantly, NSPT significantly reduced the blood level of CRP (p<0.02). However, no significant reduction in BP parameters was noted in the evaluated follow-up periods. NSPT, despite the benefits in periodontal clinical parameters, reduced the plasma level of CRP but not the BP in patients with combined RAH and periodontitis.

The goal of this study was to analyze the forest degradation in the Reserve for San Rafael National Park, Paraguay, during the period 2005-2019. This Reserve is one of the most important forest remnants of the Upper Paraná Atlantic Forest Ecoregion. A multitemporal analysis of degradation was carried out due to the occurrence of three disturbances: forest fires, a twister and illicit crops, using the Continuous Degradation Detection (CODED) algorithm, for which 3 factors were considered: variations due to pixel in the NDFI index values before, during and after every disturbance registered. In this context, the phenomenon with the greatest impact in terms of magnitude of degradation were the forest fires of 2005, being that year at the same time, the one that reported the highest degradation values. Secondly, there are the illicit crops established until the first semester of 2019, and lastly, the twister that occurred in 2017. Our findings demonstrate that CODED algorithm can detect multi-temporal degradation events in a Subtropical Broadleaf Forest, and the post-disturbance regeneration process after every disturbance tends to occur immediately. The response in terms of degradation-regeneration is highly variable, depending of the nature and severity of each disturbance and the vegetation recovery dynamics.

“De-[Constructing] Growth” is offered as a deeper and more useful conceptualization that avoids the negative connotations of, and resistance to, “degrowth” by decoupling profit from unsustainable consumption, production, and inequality.

The entropy of the partition generated by an n-tone music scale is proposed to quantify its regularity. The normalized entropy relative to a regular partition, and its complementary, here referred to as the bias, allow to analyze various conditions of similarity between an arbitrary scale and a regular scale. Interesting particular cases are scales having limited bias because their tones are distributed along interval fractions of a regular partition. The most typical case in music concerns partitions associated with well-formed scales generated by a single tone h. These scales are maximal even sets that combine two elementary intervals. Then, the normalized entropy depends on the number of tones as well as the relative size of both elementary intervals. When well-formed scales are refined, several nested families stand out with increasing regularity. It is proven that a scale of minimal bias, i.e. with less bias than those with fewer tones, is always a best rational approximation of log2h.

After brings about a brief review of the theoretical explanations and researches on the reasons for being a victim, this article is organized into two sections. The first presents a comparative analysis of the data for 1999 and 2016 in terms of perceptions, profiles and most significant sociodemographic and socioeconomic variables. The second one shows an explanatory analysis based on a multivariate logistical regression model using as an independent variable lifestyle of the population and socioeconomic variables, and as dependent variables individual’s susceptibility to becoming a victim of certain crimes. The results points towards an explanatory model of victimization in which sociodemographic variables play an increasingly less important role while variables related to lifestyle and subjective perceptions make a significant contribution to greater understanding of the nature of being the victim of a crime.

The performance of the presurgical test (preSurg) for temporal lobe epilepsy (TLE) was evaluated via video-electroencephalography (VEEG), electroencephalography (EEG), 99mTc-HmPAO single-photon emission tomography (SPECT) and 1.5 T magnetic resonance imaging (MRI) in a group of 112 men (37.0 ± 1.1 years) and 106 women (39.7 ± 1.1 years) operated on for TLE. The epileptic zone (EZ) was adequately identified to determine whether the patient reached an Engel I grade (EI) at least one year postop. Accuracy was evaluated by the coefficient α, ranging from 3 (when result = EZ) to 2 (result in the same hemisphere as the EZ), 1 (noninformative result) or 0 (EZ in the contralateral hemisphere). The simplicity of diagnosis was defined as the number of preSurg surgeries needed to identify the EZ. EI was obtained in 85.8% of patients even though 42.2% of patients had noninformative MRI results. For preSurg α was (mean ± SEM) = VEEG (2.83 ± 0.04) > MRI (2.14 ± 0.08) > EEG (1.87 ± 0.09) > SPECT (1.71 ± 0.09). The accuracy (combination of sensitivity and specificity) was calculated as follows: VEEG (0.797) > MRI (0.518) > EEG (0.446) > SPECT (0.360). The likelihood positive ratio was greater, and the likelihood negative ratio was lower for VEEG. The most relevant factor for the regression model was VEEG (3.106) > MRI (2.558) > EEG (1.905), and the factors were not significantly related to SPECT. EZs in EI patients with low simplicity were identified mainly by VEEG. A very good postoperative outcome can be obtained even in TLE patients with no lesions on MRI. The VEEG is the most reliable preSurg test and may be the only reliable test for patients with very low simplicity (i.e., difficult).single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Iron ore processing involves critical steps that affect the quality of the final product. Determining the diameter of the pellets is the necessary initial step for volume measurement and, ultimately, for porosity and bulk density measurement, crucial characteristics for optimizing the burning process in the blast furnace. Traditional measurement methods using mercury present issues related to operator safety and environmental preservation, while the practices described in ISO 4698 standard require lengthy preparation and execution time. In light of environmental needs, operator safety, and the time consumed in tests, implementing a new method based on digital image processing and convolutional neural networks for measuring the diameter of burnt iron ore pellets is proposed. The methodology involves capturing images of the pellets using a high-resolution camera and utilizing digital image processing and neural networks capable of performing pixel-by-pixel object segmentation in the images, providing precise information about the pellets to calculate their volume automatically. The results were compared with those obtained using traditional methods, evaluating their conformity with the ISO 4698 standard. In conclusion, this study offers a new approach to measuring the volume of burnt iron ore pellets, providing accurate and reliable results in compliance with safety and environmental preservation standards.

The value of landscape, as part of collective heritage, can be acquired by GIS due to the multilayer approach of the spatial configuration. Proficiency in geospatial technologies in order to collect, process, analyze, interpret, visualize and communicate geographic information is being increased by undergraduate and graduate students, but in particular by those who are training to become geography teachers at secondary education. This training can be carried out through personalized learning and distance learning methodology. Personalized GIS education aims to integrate students and enhance their understanding of landscape. Some teaching experiences are shown whereby opportunities offered by WebGIS will be described, through quantitative tools and techniques that will allow this modality of learning and improve its effectiveness. Results of this research show that students, through geospatial technologies, learn landscape as a diversity of elements but also the complexity of physical and human factors involved. Several conclusions will be highlighted: i) the contribution of geospatial training to education for sustainable development; ii) spatial analysis as a mean of skills acquisition about measures for landscape conservation; iii) expanding and applying acquired knowledge to other geographic spaces and different landscapes.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

The main objective of this article is to explore the causes of household electricity poverty in Spain from an innovative perspective. Based on evidence of energy inequality across households with different income levels, a quantile regression approach was used to better capture the heterogeneity of determinants of energy poverty across different levels of electricity expenditure. The results illustrate some interesting and counter-intuitive findings about the relationship between household income and electricity poverty, and the technical efficiency of quantile regression compared to the imprecise results of a standard single coefficient/OLS approach.

Our study analyzes the ecology and distribution of fish communities related to the environmental variables of the Alto Madre de Dios River, an Andean-Amazon watershed of southern Peru, between 300 and 2811 m a.s.l. within the Manu Biosphere Reserve. We provide new ecological and diversity data for these highly unknown rivers and new data for palm swamp habitats. With electric fishing techniques, we collected a total of 1934 fish specimens belonging to 78 species, 42 genera and 15 families. To assess main patterns of diversity we combined SIMPER and ANOSIM with canonical correspondence analysis to obtain an overview of the community structure of fish and their distribution related to aquatic habitats. Our results show an important shift on fish diversity at 700 m a.s.l. separating headwater and middle-lowland communities. Electrofishing was a hindrance due to the depth, flow and low conductivity of the rivers, but also allowed us to capture fish not observed with other techniques. We also compared the use of elevation with slope as an alternative variable for statistical analysis. Our results show that slope offers a solid and equivalent explanation for fish distribution variability, avoids redundance, and instead of giving geographical data offers ecologically solid information.

Abstract: An attractive application of crude glycerol is in the generation of biomethane by means of anaerobic co-digestion, involving the decomposition of the organic matter in two or more substrates by bacteria and archaea, in the absence of oxygen. Thus, the objective of this work was to evaluate the potential of neural networks and fuzzy logic to predict the production of biomethane from the anaerobic co-digestion of glycerol and/or sugarcane molasses. Firstly, a reactor model was implemented using Scilab, with Monod kinetics involving two substrates and an intermediate (M2SI model), to generate a database for subsequent fitting and evaluation of neural and fuzzy models. The neural network package of Matlab was used. Fuzzy modeling was applied using the Takagi-Sugeno approach available in the ANFIS package of Matlab. The biomethane production results simulated by M2SI were used in neural network modeling, firstly employing a “generic” network applicable to all 8 scenarios. A very good fit was obtained (R²>0.99). Excellent performance was also observed for specific artificial neural networks (one for each condition). The parameters of the M2SI model for the 8 different conditions were also mapped using a neural network, as a function of the organic material composition. A fit with R²>0.99 was obtained using 25 neurons. In the case of the fuzzy logic, RMSE of 18.88 mL of methane was obtained with 216 rules, which was a value lower than 0.5% of the order of magnitude of the accumulated methane. It could be concluded from the results that fuzzy logic and artificial neural networks offer excellent ability to predict methane production, as well as to parameterize the M2SI kinetic model (using neural networks).

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.

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

Microfluidic technology has become a powerful tool for several applications in chemistry, physics, biology, and engineering. Benefiting from the advantages of flowing fluids in the laminar regime, droplet-based microfluidics enable the development of various delivery systems based on food-grade emulsions, such as multiple emulsions, microgels, microcapsules, solid lipid micro-particles, and giant liposomes. Besides, by manipulating fluids on a micrometer scale with low-energy demand, it is possible to control the size, shape, and dispersity of droplets generated, which makes microfluidic emulsification an excellent strategy to modulate delivery system properties depending on the entrapped compound type. Thus, this review points out the most current advances in droplet-based microfluidic processes, in which food-grade materials were successfully utilized to develop simple and complex delivery systems. In that context, we sum-marized the principles of droplet-based microfluidics, introducing the most common microde-vices geometries, manufacturing materials, and forces involved in the different droplet generation processes within the microchannels. Subsequently, the encapsulated compound type, classified as lipophilic or hydrophilic functional compounds, was used as a starting point to present current advances in delivery systems based on food-grade emulsions and assembly using microfluidic technologies. Finally, we discuss the limitations and perspectives of scale-up in droplet-based microfluidic approaches, including the challenges that have limited the transition of microfluidic processes from lab-scale to industrial-scale.

Pesticide exposure is a growing concern for public health. Although Brazil is the world's largest consumer of pesticides, few studies addressed the health effects among farmers. This study aimed to evaluate whether pesticide exposure is associated with respiratory outcomes among rural workers and relatives in Brazil during the crop and off-seasons. 82 family farmers were interviewed about occupational history and respiratory symptoms, and cholinesterase tests were conducted in the crop-season. Spirometry was performed during the crop and off-season. Respiratory outcomes were compared between seasons and multiple regressions were conducted to search for associations with exposure indicators. Participants were occupationally and environmentally exposed to multiple pesticides from an early age. During the crop and off-season, respectively, they presented a prevalence of 40% and 30.7% for cough, 30.7% and 24% for nasal allergies, and 24% and 17.3% for chest tightness. Significant relations between spirometry impairments and exposure indicators were found both during the crop and off-season. These findings provide complementary evidence about the association of pesticide exposure with adverse respiratory effects among family farmers in Brazil. This situation requires special attention as it may increase the risk of pulmonary dysfunctions, and the morbidity and mortality burden associated with these diseases.

Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, an Inertial Measurement Unit is proposed by using a low-cost three-axis Micro-Electro-Mechanical Systems accelerometer and a GPS instrument, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to monitor indirectly the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was considered. Considering 21 km of roads, with different levels of pavement decay, validation measures made using the proposed IMU, another pre-assembled IMU, and a Road Surface Profiler were performed. Therefore, comparisons between awz determined with accelerations measured on the two different IMU are made; in addition, also correlations between awz, International Roughness Index (IRI), and Ride Number (RN) were performed. The results were shown very good correlations between the awz calculated with the proposed IMU and ones in the other IMU. In addition, the correlations between awz and IRI and RN were showed promising results, considering the use and the costs of the proposed IMU as a reliable method to assess the pavements decay in road networks where the use of traditional systems is difficult and/or not cheap.

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows to estimate direct, diffuse and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterisation techniques and allows the generation of high quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data and its resolution if two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient.

Metabolic dysfunction associated fatty liver disease (MAFLD) has gained worldwide attention as a public health problem. Nonetheless, lack of enough mechanistic knowledge restrains effective treatments. It is known that T3 regulate hepatic lipid metabolism, and mitochondrial function. Liver dysfunction of T3 contributes to MAFLD, but its role is not fully understood. Objective: To evaluate the role of T3 dysfunction in the progression of MAFLD in an animal model. Method-ology: Male/adult Sprague Dawley rats (n=20) were allocated to a control group (standard di-et–2.93kcal/g) and diet group (CDHF–4.3kcal/g). Euthanasia took place in the 28th week. D3 ac-tivity and expression, UCP2 and D1 expression, REDOX status, mitochondrial, Krebs cycle and endoplasmic reticulum homeostasis in liver tissue were measured. Results: We observed an in-crease in D3 activity/expression (P<0.001) related to increased TBARS and carbonyls and GSH reduction in the MAFLD group (P<0.05). There was a T3-dependent decrease in UCP2 expression (P=0.01), mitochondrial capacity, respiratory activity with increased endoplasmic reticulum stress in the MAFLD group (P < 0.001). Surprisingly, in and environment with lower T3 levels we observed an augmented alpha-ketoglutarate dehydrogenase (KGDH) and glutamate dehydro-genase (GDH) enzymes activity (P<0.05). Conclusion: Induced D3, triggered by changes in the REDOX state, decreases T3 availability, and hepatic mitochondrial capacity. The Krebs cycle en-zymes were altered as well as reticulum stress. Taken together, these results shed new light on the role of T3 metabolism in MAFLD and new treatment opportunities.

Despite the efforts made to stop the tuberculosis (TB) epidemic, it still remains one of the leading causes of death from an infectious disease. Previous work in the group uncovered a new family of amides which showed promising activities against Mycobacterium tuberculosis. A closer look at the literature showed that these compounds are structurally related to the DNB family of DprE1 inhibitors, so, we decided to study a wide range of substituted amides and determine their activity, focusing on unexplored structures related to the dinitrobenzamides (DNB) found in the literature. To synthesize our library of compounds we started from 3,5-dinitrobenzoic acid to form the nitroaromatic core that is characteristic of the DNB’s, to which we then added linear or cyclic amine moieties. Additionally, the impact of terminal aromatic moieties was also assessed for some derivatives, via an ether, ester, or amide bond. In order to obtain the desired derivatives, multiple synthetic approaches were used, mainly focused on nucleophilic addition/elimination reactions, SN2 reactions and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of the linker. The most interesting compounds exhibited activities comparable to isoniazid and DNB1. Computational studies were also performed aimed at understanding their possible interactions with DprE1. The most active compounds are a good starting point for further development, and we plan to study an extended family of compounds based in those structures.

Recent deep learning frameworks draw a strong research interest in the application of ego-motion estimation as they demonstrate a superior result compared to geometric approaches. However, due to the lack of multimodal datasets, most of these studies primarily focused on a single sensor-based estimation. To overcome this challenge, we collect a unique multimodal dataset named LboroAV2, using multiple sensors including camera, Light Detecting And Ranging (LiDAR), ultrasound, e-compass and rotary encoder. We also propose an end-to-end deep learning architecture for fusion of RGB images and LiDAR laser scan data for odometry application. The proposed method contains a convolutional encoder, a compressed representation and a recurrent neural network. Besides feature extraction and outlier rejection, the convolutional encoder produces a compressed representation which is used to visualise the network's learning process and to pass useful sequential information. The recurrent neural network uses this compressed sequential data to learn the relation between consecutive time steps. We use the LboroAV2 and KITTI VO datasets to experiment and evaluate our results. In addition to visualising the network's learning process, our approach gives superior results compared to other similar methods. The code for the proposed architecture is released in GitHub and accessible publicly.

The objective of this study was to carry out the extraction and characterization of chitin and chitosan from the exoskeletons of the Farfantepenaeus californiensis species of shrimp, as well as its application in the formulation of polymeric films plasticized with glycerol used in the process of food packaging. The characterization of the extracted polymer was made by Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and physicochemical analysis of chitin and chitosan, resulting in a theoretical performance of 29.33% and 16.46%, respectively. In terms of quality, it was determined that the extracted chitosan had a molecular weight of 1.10 x105 g/mol and a deacetylation degree of 80.23%, which classifies it as a low-molecular weight chitosan, suitable for food packaging. It was shown that the extracted chitosan is fit for the production of the films by using the casting method, presenting a tension resistance of 1 MPa. The Antibacterial analysis was carried out using Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), bacterial models commonly found in food. The results showed an effective inhibition capability of the polymeric materials. Overall, the results for both chitosan and the films indicate a high potential for application in the food packaging sector.

An explanation of the origin of dark matter is suggested in this work. The argument is based on symmetry considerations about the concept of mass. In the Wigner's view, the rest mass and the spin of a free elementary particle in flat space-time are the two invariants that characterize the associated unitary irreducible representation of the Poincar\'e group. The Poincar\'e group has two and only two deformations with maximal symmetry. They describe respectively the de Sitter (dS) and Anti de Sitter (AdS) kinematic symmetries. Analogously to their shared flat space-time limit, two invariants, spin and energy scale for de Sitter and rest energy for Anti de Sitter, characterize the unitary irreducible representation associated with dS and AdS elementary systems. While the dS energy scale is a simple deformation of the Poincaré rest energy and so has a purely mass nature, AdS rest energy is the sum of a purely mass component and a kind of zero-point energy derived from the curvature. An analysis based on recent estimates on the chemical freeze-out temperature marking in Early Universe the phase transition quark-gluon plasma epoch to the hadron epoch supports the guess that dark matter energy might originate from an effective AdS curvature energy.

Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.

This paper presents two designs of high-efficiency polarizer reflectarray antennas able to generate a collimated beam in dual-circular polarization using a linearly polarized feed, with application to high-gain antennas for data transmission links from a Cubesat. First, an 18 cm x 18 cm polarizer reflectarray operating in the 17.2 - 22.7 GHz band has been designed, fabricated and tested. The measurements of the prototype show an aperture efficiency of 52.7% for right-handed circular polarization (RHCP) and 57.3% for left-handed circular polarization (LHCP), both values higher than those previously reported in related works. Then, a dual-band polarizer reflectarray is presented for the first time, which operates in dual-CP in the frequency bands of 20 and 30 GHz. The proposed antenna technology enables a reduction of the complexity and cost of the feed chain to operate in dual-CP, as a linear-to-circular polarizer is no longer required. This property, combined with the lightweight, flat profile and low fabrication cost of printed reflectarrays, makes the proposed antennas good candidates for Cubesat applications.

Epidemiological studies have shown that consuming olive oil rich in phenolic bioactive compounds is associated with a lower risk of neurodegenerative diseases and better cognitive performance in aged populations. Since oxidative stress is a common hallmark of age-related cognitive decline, incorporating exogenous antioxidants could have beneficial effects on brain aging. In this review, we firstly summarize and critically discuss the current preclinical evidence and the potential neuroprotective mechanisms. Existing studies indicates that olive oil phenolic compounds can modulate and counteract oxidative stress and neuroinflammation, two relevant pathways linked to the onset and progression of neurodegenerative processes. Secondly, we summarize the current clinical evidence. In contrast to preclinical studies, there is no direct evidence in humans of the bioactivity of olive oil phenolic compounds. Instead, we have summarized current findings regarding nutritional interventions supplemented with olive oil on cognition. A growing body of research indicates that high consumption of olive oil phenolic compounds is associated with better preservation of cognitive performance, conferring an additional benefit, independent of the dietary pattern. In conclusion, the consumption olive oil rich in phenolic bioactive compounds has potential neuroprotective effects. Further research is needed to understand the underlying mechanisms and potential clinical applications.

Conyza canadensis is a species invading large agricultural areas throughout the world, mainly to its ability to evolve herbicide resistance. Specifically, in Hungary, extensive areas have been infested by this species due to the difficulty in controlling it with glyphosate. To corroborate this fact as resistance and not as an incorrect herbicide application, eight suspicious glyphosate-resistant C. canadensis populations from different Hungarian regions were studied. In dose-response assays with glyphosate, the LD50 and GR50 values indicated that populations 1 to 5 were resistant to this herbicide (H-5 population the most resistant). Besides, the shikimic acid accumulation tests corroborated the results observed in the dose-response assays. 11 alternative herbicides from 6 different mode of action (MOA) were applied at field doses as control alternatives on populations H-5 and H-6 (both in the same regions). The H-5 population showed an unexpected resistance to flazasulfuron (ALS-inhibitor). The ALS enzyme activity studies indicated that the I50 for H-5 was 63.3 fold higher compared to its correspondent susceptible population (H-6). Therefore, the H-5 population exhibited multiple-resistance to flazasulfuron and glyphosate, being the first case reported in Europe for this two MOA. For that reason, the other herbicides with different MOA have to be tested here.

The electronic structure of 7/9-AGNR superlattices with up to eight unit cells has been studied by means of state of the art Density Functional Theory (DFT) and also by two model Hamiltonians, the first one including only local interactions (Hubbard model, Hu) while the second one is extended to allow long-range Coulomb interactions (Pariser, Parr and Pople model, PPP). Both are solved within mean field approximation. At this approximation level, our calculations show that 7/9 interfaces are better described by spin non-polarized solutions than by spin-polarized wavefunctions. Consequently, both Hu and PPP Hamiltonians lead to electronic structures characterized by a gap at the Fermi level that diminishes as the size of the system increases. DFT results show similar trends although a detailed analysis of the density of states around the Fermi level shows quantitative differences with both Hu and PPP models. Before improving model Hamiltonians, we interpret the electronic structure obtained by DFT in terms of bands of topological states: topological states localized at the system edges and extended bulk topological states which interact between them due to the long-range Coulomb terms of Hamiltonian. After careful analysis of the interaction among topological sates, we find that the discrepancy between ab initio and model Hamiltonians can be resolved considering a screened long-range interaction that is implemented adding an exponential cutoff to the interaction term of PPP model. In this way, an adjusted cutoff distance λ = 2 allows a good recovery of DFT results. In view of this, we conclude that the correct description of the density of states around the Fermi level (Dirac point) needs the inclusion of long-range interactions well beyond Hubbard model but not completely unscreened as is the case for the PPP model.

During the last years there has been a high interest in the development of new purely-organic single-component conductors. Very recently, we have reported a new neutral radical conductor based on the perchlorotriphenylmethyl (PTM) radical moiety linked to a monopyrrolo-tetrathiafulvalene (MPTTF) unit by a -conjugated bridge (1). Interestingly, this system behaves as a semiconductor with high conductivity and small energy gap under high pressure. With the aim of developing a new material with improved conducting properties, we have designed and synthesized the radical dyad 2 which was functionalized with an ethylenedithio (EDT) group in order to improve the intermolecular interactions of the TTF subunits. The physical properties of the new radical dyad 2 were studied in detail in solution to further analyze its electronic structure as well as its potential use as radical conductor in the solid state.

Biopolymers based on plant and animal proteins are interesting alternatives in the development of films with future prospects as food packaging. Considering that in recent years there has been an increasing interest in the valorization of agro-industrial residues and by-products and that the blending of polymers can lead to materials with improved properties, in this work, keratin-rich feather fibers and gliadins were blended at different ratios in order to develop sustainable and biodegradable films. Control gliadin G100, feather F100 films and their blends at 3:1 (G75F25) , 2:2 (G50F50) and 1:3 (G25F75) ratios were successfully developed through thermoprocessing. The physical properties were differentiated as a function of the concentration of both polymeric matrices. Although gliadins showed higher hydrophilicity confirmed by its highest swelling degree, films with high gliadin ratios exhibited lower water permeability values at low and medium relative humidities. On the other hand, the feathers displayed the highest Young´s modulus values and provided oxygen barrier to the blends, principally at the highest relative humidity. In conclusion, the blend of these protein-based polymers at different ratio resulted on interesting composites whose physical properties could be adjusted.

Objectives: This study aims to explore the use of murine models in peripheral nerve transection research, evaluating and synthesizing key methods for analyzing nerve regeneration to guide future research and clinical interventions. Methodology: A systematic review was conducted in February 2024, adhering to Cochrane and PRISMA 2020 guidelines, using Medline, Scielo, and Lilacs databases. The focus was on experimental studies of nerve regeneration in animal models post-transection. Only experimental clinical trials reporting nerve regeneration outcomes were included; studies lacking a comparator group or functional evaluation methods were excluded. Results: Out of 273 studies initially identified from MEDLINE, 19 were selected for detailed analysis. The average study included 32.5 subjects, with about 10.16 subjects per intervention subgroup. The predominant model was the sciatic nerve injury with a 10mm gap. The most common intervention involved unprocessed adipose-derived stem cells, utilized in 14 articles. Conclusions: The review underscores the significant potential of current methodologies in peripheral nerve regeneration, particularly highlighting the use of murine models and thorough evaluation techniques. These studies significantly contribute to our understanding of nerve regeneration processes and inform directions for future research.

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

This study aimed to evaluate the physico-chemical properties, biocompatibility and bioabsorption of 3 different new membranes for bone guided regeneration (PLGA associated with hydroxyapatite and beta-TCP) with three thicknesses (200, 500 and 700 µm) implanted in mice subcutaneously. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and the quantification of Carbon, Hidrogen and Nitrogen were used to characterize the physico-chemical properties. One hundred Balb-C mice were divided into 5 experimental groups: Group 1 - Sham (without implantation); Group 2 - 200 μm; Group 3 - 500 μm; Group 4 - 700 μm; and Group 5 - Pratix®. Each group was subdivided into four experimental periods (7, 30, 60 and 90 days). Samples were collected and processed for histological and histomorphometrical evaluation. The membranes showed no moderate or severe tissue reactions in the experimental periods studied. The 500 μm membrane did not show tissue reaction for any experimental periods studied. The 200 μm membrane membranes began to exhibit fragmentation after 30- day, while the 500 and 700 µm membranes started the fragmentation at 90-day. All membranes studied were biocompatible, and the 500µm membrane showed the best results being a promissory membrane for bone guided regeneration.

Health differences across socioeconomic strata have always pointed out that poorer and minorities have higher mortality and morbidity than richer and majorities. This difference is exacerbated for particular populations such as the victims of ongoing armed conflicts, who are also much harder to quantify due to the conflict itself. This study applies network analysis to a combination of three large administrative records for the health system and mortality records in the province of Risaralda (Colombia) between 2011 and 2016. It produces the most common causes of morbi-mortality for both victims of violence and the poorest inhabitants of Risaralda, defined as those who qualify as recipients of subsidies from the Colombian welfare program called SISBEN in the categories of highest need. Both populations show high morbidity frequencies for non-communicable diseases such as Type II diabetes, hypertension, and hyperglyceridaemia, mostly associated with exposure to unhealthy lifestyles. Additionally, the mortality outcomes reflect the different lifestyles and medical treatments of both subpopulations. While the poorest replicate the same causes identified for morbidity, the victims of armed conflict die of additional causes including Type II diabetes, which reflects the even worse conditions they face.

Unmanned aerial vehicles (UAVs) represent a new model of social robots for home care of dependent persons. In this regard, this article introduces a study on people’s feeling of safety and comfort while watching the monitoring trajectory of a quadrotor dedicated to determining their condition. Three main parameters are evaluated: the relative monitoring altitude, the monitoring velocity and the shape of the monitoring path around the person (ellipsoidal or circular). For this purpose, a new trajectory generator based on a state machine, which is successfully implemented and simulated in MATLAB/Simulink®, is described. The study is carried out with 37 participants using a virtual reality (VR) platform based on two modules, UAV Simulator and VR Visualiser, both communicating through the MQTT protocol. The participants’ preferences have been a high relative monitoring altitude, a high monitoring velocity and a circular path. These choices are a starting point for the design of trustworthy socially assistive UAVs flying in real homes.

As a form of protection, a nature park is often created to protect and valorise natural and cultural heritage in peripheral rural areas. However, in terms of multi-functionality, new nature parks are incorporated into traditional productive activities, such as recreational and tourist activities, which sometimes compromise sustainability. The research objective is to study the relationship between tourism and sustainability in the Nature Parks of “Sierra de Aracena y Picos de Aroche”, “Sierra Norte de Sevilla” and “Sierra de Hornachuelos” that makes up the Dehesas de Sierra Morena Biosphere Reserve in Andalusia, Spain. Therefore, selective interviews have been carried out with the stakeholders to establish their perception of sustainable tourism and the presence of dominant discourses. The main conclusions indicate (1) the presence of different dominant discourses on sustainability, namely the conservationist and mercantilist ones, with the prevalence of the economic dimension; (2) poor awareness and adaptation to the context of global change; and (3) the presence of competitive relationships that generate difficulties for the governance of sustainable tourism.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

French Guiana, located in the Guiana Shield, is a natural reservoir for many zoonotic pathogens that are of considerable medical or veterinary importance. Until now, there are few data available on the description of parasites circulating in this area, especially on protozoan belonging to the phy-lum Apicomplexa; conversely, the neighbouring countries describe a high parasitic prevalence in animals and humans. Epidemiological surveillance is necessary, as new potentially virulent strains may emerge from these forest ecosystems, such as Amazonian toxoplasmosis. However, there is no standard tool for detecting protozoa in wildlife. In this study, we developed Meat-Borne-Parasite, a high-throughput meta-barcoding workflow for detecting Apicomplexa based on Oxford Nanopore Technologies sequencing platform using the 18S gene of fourteen Apicomplexa-positive samples collected in French Guiana. Sequencing reads were then analysed with MetONTIIME pipeline. Thanks to a scoring rule, we were able to classify as Apicom-plexa-positive 10 samples out of 14 and reveal the presence of co-carriages. The same samples were also sequenced with Illumina platform, for validation purposes. On samples identified as Apicomplexa-positive by both platforms, a strong positive correlation at up to genus level was reported. Overall, the presented workflow represents a reliable method for Apicomplexa detec-tion, which may pave the way for more comprehensive biomonitoring of zoonotic pathogens.

We discuss the consequences of the unique symmetry of the de Sitter spacetime. This symmetry leads to the specific thermodynamic properties of the de Sitter vacuum, which produces the thermal bath for matter. The de Sitter spacetime is invariant under the modified translations, ${\bf r}\rightarrow {\bf r} -e^{Ht}{\bf a}$, where $H$ is the Hubble parameter. For $H\rightarrow 0$, this symmetry corresponds to the conventional invariance of Minkowski spacetime under translations ${\bf r}\rightarrow {\bf r} -{\bf a}$. Due to this symmetry, all the comoving observers at any point of the de Sitter space perceive the de Sitter environment as the thermal bath with temperature $T=H/\pi$, which is twice larger than the Gibbons-Hawking temperature of the cosmological horizon. This temperature does not violate the de Sitter symmetry, and thus does not require the preferred reference frame, as distinct from thermal state of matter, which violates the de Sitter symmetry. This leads to the heat exchange between gravity and matter, and to instability of de Sitter state towards the creation of matter, its further heating, and finally to the decay of the de Sitter state. The temperature $T=H/\pi$ determines different processes in the de Sitter environment, which are not possible in the Minkowski vacuum, such as the process of ionization of an atom in the de Sitter environment. This temperature also determines the local entropy of the de Sitter vacuum state, and this allows us to calculate the total entropy inside the cosmological horizon. The result reproduces the Gibbons-Hawking area law, which is related to the cosmological horizon, $S_{\rm hor}=4\pi KA$, where $K=1/16\pi G$. This supports the holographic properties of the cosmological event horizon. We extend the consideration of the local thermodynamics of the de Sitter state using the $f({\cal R})$ gravity. In this thermodynamics, the Ricci scalar curvature ${\cal R}$ and the effective gravitational coupling, $K$, are thermodynamically conjugate variables. The holographic connection between the bulk entropy of the Hubble volume, and the surface entropy of the cosmological horizon remains the same, but with the gravitational coupling $K=df/d{\cal R}$. Such connection takes place only in the $3+1$ spacetime, where there is the special symmetry due to which the variables $K$ and ${\cal R}$ have the same dimensionality. We also consider the lessons from the de Sitter symmetry for the thermodynamics of black and white holes.

This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study. We explore the practical implementation of digital twins and their efficacy in optimizing operations and predictive maintenance. Our findings emphasize digital twins' potential as a valuable tool for renewable energy, driving efficiency and sustainability in offshore floating wind installations.

This study aims to examine the non-volatile Particle Number (PN) emissions of a retrofitted Heavy-Duty Spark-Ignition (HD-SI) engine powered by liquefied petroleum gas (LPG) under both steady-state and transient conditions. The engine was tested under seven steady-state operating points to investigate the PN behavior and Particle Size Distribution (PSD) upstream and down-stream of the Three-Way Catalyst (TWC). This analysis intends to assess the impact of including particles with diameters ranging from 10 nm to 23 nm in the total particle count, a consideration for future regulations. The study employed the World Harmonized Transient Cycle (WHTC) for transient conditions to encompass the same engine working region used in the steady-state analysis. A Dekati FPS-4000 diluted the exhaust sample to measure the PSD and PN for particle diameters between 5.6 nm and 560 nm using the TSI-Engine Exhaust Particle Sizer (EEPS) 3090. Findings indicate that PN levels tend to increase downstream of the TWC under steady-state conditions in operating points with low exhaust gas temperatures and flows (equal to or less than 500 °C and 120 kg/h). Furthermore, the inclusion of particles with diameters between 10 nm and 23 nm leads to an increase in PN emissions by 17.70% to 40.84% under steady conditions and by an average of 40.06% under transient conditions, compared to measurements that only consider particles larger than 23 nm. Notably, in transient conditions, most PN emissions occur during the final 600 seconds of the cycle, linked to the most intense phase of the WHTC.

Recurrent pregnancy loss (RPL) affects around 2 % of women of reproductive age. Primary RPL is defined by ≥2 pregnancy losses and no normal birth delivery. In secondary RPL, the losses are after a normal pregnancy and delivery. Most cases have no clear aetiology, although primary cases are the most complex. Several gene polymorphisms have been associated with RPL. Some polymorphisms are increased in women of Asian or Caucasian race. In admixed RPL populations, the information on possible genetic links is scarce and contradictory. The study aimed to assess the frequency of two SNP in different enzymes involved in medical conditions observed during pregnancy. Microsomal epoxy hydrolase (mEPH) is involved in detoxifying xenobiotics. It is present in ovaries, and it is hormonally regulated. The endothelial nitric oxide synthase forms nitric oxide from arginine and is involved in vascular tone. Two SNPs, rs1051740 and rs1799983, were assessed. The study included 26 controls and 63 primary RPL patients. Significant differences were observed in the frequencies of both SNP (p<0.05). The frequency of mutated alleles was higher in patients. Double mutated homozygotes were encountered only in RLP patients (p<0.05). Genetic polymorphisms rs1051740 and rs1799983 may be involved in primary RPL in the Venezuelan admix population. Genetic studies could provide crucial information on the aetiology of primary RPL.

Human pigmentation has been largely associated with different disease prevalence among populations, but most of these studies are observational and inconclusive. Known to be genetically determined, pigmentary traits have been largely studied by GWAS, mostly in Caucasian ancestry cohorts from North Europe, identifying robustly, several loci involved in many of the pigmentary traits. Here, we conduct a detailed analysis of 13 pigmentary-related traits in a South European cohort of Caucasian ancestry (n=20,000). We observed fair phototype strongly associated with non-melanoma skin cancer and other dermatoses and confirmed by PRS-approach the shared genetic basis with skin and eye diseases, such as melanoma (OR=0.95), non-melanoma skin cancer (OR=0.93), basal cell carcinoma (OR=0.97) and darker phototype with vitiligo (OR=1.02), and cataracts (OR=1.04). Detailed genetic analyses revealed 37 risk loci associated with 10 out of 13 analyzed traits, and 16 fine-mapped genes significantly associated with at least two pigmentary traits. Some of them widely reported, such as MC1R, HERC2, OCA2, TYR, TYRP1, SLC45A2, and unveiling three new candidates RP11-1084J3.4, C1QTNF3 and C17orf112, not reported in GWAS Catalog. These results highlight the importance of phototype assessment as a genetic proxy of skin functionality when evaluating disease screening in mixed populations.

Beaches are among the habitats most frequented by migratory birds for breeding and/or wintering. However, threats such as human pressure and sea level rise can reduce the availability of these habitats for different species. The presence of alternative areas, such as salt pans and brackish habitats, is essential for many migratory shorebird populations. This study addresses the post-breeding dispersal of the Kentish plover (Charadrius alexandrinus) in the Iberian Peninsula by analysing C and N isotopes in feathers. The study was conducted at six locations along the Iberian coast, which were categorized in three areas: NW Atlantic coast, the Atlantic coast of Andalusia and the Mediterranean coast. Although linear mixed models did not reveal any significant effects of sex or coastal area on isotopic levels, the variability in the data suggests different habitat-use strategies in the post-reproductive period. Birds from the northwest of the Iberian Peninsula exhibit greater fidelity to a single habitat type, i.e. coastal beaches, while populations from the Mediterranean coast and the Atlantic coast of Andalusia show different individual dispersal strategies, occupying coastal habitats and freshwater wetlands. The lack of alternative habitats for the northwest Iberian population, the reduction in available habitat due to rising sea levels and human pressure together pose a serious threat to the survival of this species, already with an unfavourable conservation status.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

The production of fuels and other industrial products from renewable sources has intensified the search for new substrates or for the expansion of the use of substrates already in use, as well as the search for microorganisms with different metabolic capacities. In the present work, we isolated and tested a yeast from the soil of sugarcane irrigated with vinasse, that is, with high mineral content and acidic pH. The strain of Meyerozyma caribbica URM 8365 was able to ferment glucose, but the use of xylose occurred when some oxygenation was provided. However, some fermentation of xylose to ethanol in oxygen limitation also occurs if glucose is present. This strain was able to produce ethanol from molasses substrate with 76% efficiency, showing its tolerance to possible inhibitors. High ethanol production efficiencies were also observed in acidic hydrolysates of each bagasse, sorghum, and cactus pear biomass. Mixtures of these substrates were tested and the best composition was found for the use of excess plant biomass in supplementation of primary substrates. It was also possible to verify the production of xylitol from xylose when the acetic acid concentration is reduced. Finally, the proposed metabolic model allowed calculating how much of the xylose carbon can be directed to the production of ethanol and/or xylitol in the presence of glucose. With this, it is possible to design an industrial plant that combines the production of ethanol and/or xylitol using combinations of primary substrates with hydrolysates of their biomass.

Among the leading immersive technologies, Augmented Reality is one of the most promising and empowering to support designers in production environments. This research investigates the application of mobile augmented reality, based on the Web, as a mediation tool focused on cognitive activities of reading and understanding of Technical Drawings in the production and assembly for Tailor Made projects of the scenographic industry. In this context, the research presents a method to use the WebAR to improve the reading of technical drawings, seeking efficiency on the visualization of models and the exchange of information between professionals, involved in the processes of design, production and assembly of products, in the scope of scenography. This mediation tool was developed using Web AR platforms, compatible with native libraries (ARCore and ARKit) to ensure, first, compatibility with commonly used devices that workers or businesses can access, and secondly, to leverage hybrid tracking techniques that combine vision and sensors to improve the reliability of augmented reality viewing. The proposed solution adopts multiple tracking and navigation techniques in order to expand Space Skills components to provide greater exploratory freedom to users. The research process took place in the light of the Design Science Research Methodology and the DSR-Model, since it aimed to develop a solution to a practical problem, as well as to produce knowledge from this process. Field experiments were conducted in two real companies, with end users on their respective mobile devices, in order to evaluate usability and behavioral intent, through the Acceptance, Intent and Use of Technology questionnaires; and perceived mental workload, NASA-TLX. The experimental results show that the adoption of this tool reduces the cognitive load in the process of reading technical drawings and project´s understanding. In general, it´s usability and intent to use provide significant levels of satisfaction, being positively accepted by all participants involved in the study.

Leishmaniasis in wild canids is a vector-borne disease caused in Europe by the protozoan parasite Leishmania infantum. To date, there is limited information on clinical signs and laboratory abnormalities in wolves due to leishmaniasis. The current clinical case report described a female Iberian wolf (Canis lupus signatus) housed in semi-captivity conditions at the Centro del Lobo Ibérico “Félix Rodríguez de la Fuente”, in Robledo de Sanabria, Zamora (Spain) with an interdigital ulcerous wound at the right forepaw, hyper-gammaglobulinemia, and abnormal liver blood parameters. Definitive serodiagnosis of leishmaniasis was established using antileishmanial serum antibodies and PCR analysis of different biological samples. A gold standard anti-L. infantum treatment protocol consisting in intramuscular meglumine antimoniate and oral allopurinol combination was installed. However, the presence of pain at the site of injection due to meglumine antimoniate administration forced its substitution by oral miltefosine. A progressive reduction of the levels of anti-L. infantum serum antibodies and the concentrations of gamma-globulin fraction was detected after antileishmanial treatment as well as a decline of liver GPT. To our knowledge, this is the first case of leishmaniasis diagnosed in a wolf housed in semi-captivity conditions treated and successfully cured.

Some of the European countries affected by COVID-19 have not learned from previous experience in China. Italy did not learn from China and Spain did neither learn from China nor from Italy. Confinement in Spain was postponed due to pressure from economic interests and traveling of infected people, especially from Madrid to the beaches in South-East Spain, was allowed. Strict confinement and border closure came late, when the curve of infected people and the death toll already had the worse trend worldwide. Tests to SARS-CoV-2 RNA detection by PCR, were first unavailable and, later, faulty and/or detecting antibodies and not the virus itself. Instead of mobilizing research laboratories for making tests, and instead of making masks and ventilators, mediatic scientists asked for money for controversial clinical trials and for obtaining a vaccine. In this scenario, common sense indicates that ad hoc measures should be taken at the end of confinement in order to minimize pain. The chain of errors should be avoided in the management of next pandemics by designing Good Practice Rules (GPRs). In addition, post-confinement measures should be implemented as soon as possible to be ready for SARS-CoV-2 return next season. In this sense a longitudinal study in the most affected cities (Madrid, Barcelona, Vitoria and Pamplona) should be performed with the primary objective of detecting carriers with no symptoms, to stratify patients according to symptoms, and to early detection of virus reappearance. Also relevant is to sequence as many viruses as possible to detect possible variants; there are still patients that are PCR positive.

The aim of the present study was to investigate the acute effect of caffeine supplementation on performance in official soccer matches. In double-blind, randomized crossover design, 13 professional soccer players performed two complete matches, with Caffeine (CAF) (6 mg/kg) and placebo (PLA) supplementation. Two-way repeated measures ANOVA showed that there was no effect of supplementation on the total distance covered (p = 0.536; ŋp² =0.033) or the total distance covered at different speeds (p = 0.453; ŋp² = 0.048), acceleration or deceleration (p = 0.387; ŋp² = 0.063) number of sprints (p = 0.521; µ² = 0.035) Heart Rate mean (p = 0.484; ŋp² = 0.042) Heart Rate maximum (p = 0.110; ŋp² = 0.199), Rate Perceived Effort (p = 0.151) or efficiency index (p = 0.480). Therefore, acute caffeine supplementation not effective to increase the performance of soccer players in official matches.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting both the evolution of this field and its integration to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, the review sheds light on the potential implications of WBT for the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation with the EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

Mathematical algorithms relate satellite data of ocean color with the surface Chlorophyll–a con-centration (Chl-a), a proxy of phytoplankton biomass. These mathematical tools work best when they are adapted to the unique bio-optical properties of a particular oceanic province. Ocean color algorithms should also consider that there are significant differences between datasets derived from different sensors. Common solutions are to provide different parameters for each sensor or use merged satellite data. In this paper we use satellite data from the Copernicus merged product suite and in situ data from the southernmost part of the California Current System to test two widely used global algorithms, OCx and CI, and a regional algorithm, CalCOFI2. The OCx al-gorithm gave the best result, therefore, it was regionalized and, again, tested. The database was then separated according to (a) dynamic boundaries in the area, (b) bio-optical properties and (c) climatic condition (El Niño/La Niña). Regional algorithms were obtained and tested for each partition. The Chl-a retrievals for each model were tested and compared. The best fit for the data was for the regional algorithms that considered the climatic conditions (El Niño/La Niña). These results will allow the construction of consistent regionally adapted time-series and, therefore, demonstrates the importance of El Niño/La Niña events on the bio-optical properties of the area.

Background: Alzheimer's Disease (AD) is a progressive and incurable condition that prompts the exploration of interventions to slow its advancement and enhance the quality of life. The cortical brain waves could have a role in the process of executive function deterioration, increasing dementia symptoms. Objective: To interrogate the effects of physical exercise, and non-invasive brain stimulation, both in electrophysiological behavior of the brain, the executive functions, and dementia symptoms in older adults with AD. Methods: One hundred and sixteen older adults were grouped (n=22 each): GAE (AD, PMED+NIBS), GCP (AD, PMED), GCN (AD, NIBS), GCS (control, no intervention). Binaural beats were used as a non-invasive brain stimulation, physical exercise, or both, were applied during 16 weeks. Pre/post measurements included Alpha Band, and SMR Rhythms, executive functions, and dementia symptoms. Results: GCS showed no significant changes (p>0.05). GCN and GCS slightly enhanced inhibitory control (p>0.05) and working memory (p>0.05). In contrast, GCP and GAE improved executive function (p

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.

(1) Background: The severity of malaria is associated with low bioavailability of antioxidants and high concentration of free radicals that induce oxidative damage in cerebral and pulmonary microcirculation. This can be prevented by the action of consumable antioxidants present in foods. Therefore, we investigated the protective role of lycopene (LYC) on the oxidative changes induced by Plasmodium berghei (Pb); (2) Methods: Mice were infected by intraperitoneal injection of 106 parasitized red blood cells and treated via gavage with LYC (3.11 mg/kg bw/day) or NAC (62 mg/kg bw/day). They were then evaluated for 1, 4, 8 or 12 days after infection. Levels of thiobarbituric acid reactive substances (TBARS), antioxidant capacity by inhibition of ABTS radicals (AC-ABTS) and DPPH (AC-DPPH), uric acid (UA), and nitric oxide (NO) were measured in brain and lung tissues; (3) Results: The infection caused oxidative stress confirmed by increased levels of TBARS, AC-ABTS, AC-DPPH, UA, and NO in the tissues leading to the death of the animals. LYC prevented the increase in TBARS, AU, and NO levels compared to Pb (p&lt; 0.0001) and NAC+Pb groups (p&lt;0.0001), reaching values similar to those of Sham animals; (4) Conclusions: These results are striking evidence of the beneficial effect of lycopene supplementation on oxidative stress in experimental malaria in vivo and emphasize the importance of antioxidant supplementation in the treatment of the disease.

In this article we propose an application of humanitarian logistics theory to build a supportive framework for economic reactivation and pandemic management based on province vulnerability against COVID-19. The main research question is: which factors are related to COVID-19 mortality between Peruvian provinces? We conduct a spatial regression analysis to explore which factors determines the differences in COVID-19 cumulative mortality rates for 189 Peruvian provinces up to December 2020. The most vulnerable provinces are characterized by having low outcomes of long-run poverty and high population density. Low poverty means a high economic activity that leads to more deaths of COVID-19. There is a lack of supply of a set of relief goods defined as Pandemic Response and Recovery Supportive Goods and Services (PRRSGS). These goods must be delivered in order to mitigate the risk associated to COVID-19. A supportive framework for economic reactivation can be built based on regression results and a delivery strategy can be discussed according to the spatial patterns that we found for mortality rates.

This article presents and discusses analytical data on the scientific publication record from 1910 to 2020 on two topics: "climate" and "climate change/global warming/climate emergency". The goal is to visualize how the publication record on these two topics has evolved over time, from different classification perspectives (year, country, source and organization). Three hypotheses are tested using data collected from Web of Science and various graphical representations of the data. It is found that research output related to the Earth’s contemporary changing climate overtook that of general climate research in 2011, and the publication ratio has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics, and conversely less significant differences in terms of organizations publishing these works. Differentiation factors that affect the level of research output and engagement on the climate challenge include: island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as “climate emergency”.

Optical backbone networks constitute the fundamental infrastructure employed today by network operators to deliver services to users. As network capacity is a key factor influencing optical network performance, it is important to understand how topological and physical properties impact its behavior and to have the capability to estimate its value. In this context, we propose here a method to evaluate the network capacity that relies on the optical reach to account for physical layer aspects, in conjunction with constrained routing techniques for traffic routing. As this type of routing can lead to traffic blocking, particularly due to the limitation on the number of wavelengths per fiber, we also propose a fiber assignment algorithm designed to deal with this problem. We apply this method to a set of randomly generated networks using a modified Waxman model, and for a network with 60 nodes, in a scenario without blocking, we obtain capacities of about 2.5 Pbit/s for a symbol rate of 64 Gbaud and about 5 Pbit/s for a symbol rate of 128 Gbaud. Remarkably, this duplication in the total network capacity is achieved by an increase in the total fiber length of only about 51%.

Proteins play a pivotal role in supporting athletes by promoting muscle hypertrophy and minimizing protein catabolism during exercise. They stimulate muscle protein synthesis, aiding in the repair of exercise-induced muscle damage and serving as an energy source, particularly for post-exercise glycogen replenishment. In individuals with phenylketonuria (PKU), for whom protein intake is limited to essential phenylalanine (Phe), supplementation with Phe-free amino acids or glycomacropeptides is necessary. Tailored for macronutrient and micronutrient content, these protein substitutes fulfill most protein requirements, but lack Phe, unlike dietary sources of protein. Protein requirements for athletes with PKU exceed general recommendations due to limited availability in supplements and potential catabolism mitigation. Various factors influence tolerated dietary Phe in PKU, including protein substitute quantity, distribution, pharmacological treatment, age, growth rate, pregnancy, catabolic states, and physical activity. While general protein requirements for PKU surpass those of the general population, adherence to supplement regimens is crucial for athletes and patients with PKU. Strategically timed protein substitutes enhance muscle protein synthesis, body composition, and sports performance within safety limits. Individualized intake is essential for optimal outcomes, as proteins have a multifaceted role in optimizing athletic performance and addressing challenges in PKU.

Most Neotropical Psittacidae have a diploid number of 2n=70, and a dichotomy in chromosome patterns. Long-tailed species have biarmed macrochromosomes, while short - tailed ones have telo/acrocentric macrochromosomes. However, the use of chromosome painting with chicken and white hawk probes has demonstrated that karyotype evolution in Psittacidae includes a high number of inter/intrachromosomal rearrangements. Hence, to determine the phylogeny of Long and Short-Tailed species, and to propose a putative ancestral karyotype for this group, we constructed homology maps of Pyrrhura frontalis (PFR) and Amazona aestiva (AAE) and compared them to other previously analyzed long-tailed species. Chromosomes were analyzed by conventional staining and fluorescent in situ hybridization (FISH) using whole chromosome paints of G. gallus (GGA) and L. albicollis (LAL). Conventional staining showed a karyotype with 2n=70 in both species, with biarmed macrochromosomes in Pyrrhura frontalis and telo/acrocentric chromosomes in Amazona aestiva. Comparison of the results with the putative avian ancestral karyotype (PAK) showed fusions in P. frontalis of PAK1p/PAK4q (PFR1) and PAK6/PAK7 (PFR6) with a paracentric inversion in PFR6. However, in A. aestiva there was only the fusion between PAK6/7 (AAE7) with a paracentric inversion. Hybridizations with LAL probes confirmed these results. The results indicate that PFR retained a more basal karyotype than Anodorhynchus hyacinthinus (AHY), Ara macao (AMA) and Ara chloropterus (ACH), because these three species show the fusion PAK8/PAK9 that is not seen in PFR. Hence, we suggest that the ancestral karyotype of species with biarmed chromosomes have the fusions PAK1p/PAK4 and PAK6/PAK7 and, additionally, a pericentric inversion of PAK6/PAK7, while the fusion PAK8/PAK9 would have appeared in the common ancestor of Anodorhynchus hyacinthinus, Ara macao and Ara chloropterus. However, the species A. aestiva shows a characteristic plesiomorphic trait, since PAK1p/PAK4q and PAK8/9 fusions are absent. Our results base on chromosome rearrangements suggest the classification following the criterium of tail length may no reflect the real phylogenetic history of Neotropical Psittacidae.

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electricity power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electricity power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

A review of quantitative risk assessment (QRA) models of L. monocytogenes in produce was carried out, with the objective of appraising and contrasting the effectiveness of the control strategies placed along the food chains. Despite nine of the thirteen QRA models recovered focused on fresh or RTE leafy greens, none of them represented important factors or sources of contamination in the primary production, such as type of cultivation, water, fertilisers or irrigation method/practices. Cross-contamination at processing and during consumer’s handling was modelled using transfer rates, which were shown to moderately drive the final risk of listeriosis; highlighting therefore the importance of accurately representing the transfer coefficient parameters. Many QRA models coincided in the fact that temperature fluctuations at retail or temperature abuse at home were key factors contributing to increasing the risk of listeriosis. In addition to a primary module that could help assess current on-farm practices and potential control measures, future QRA models for minimally-processed produce should also contain a refined sanitisation module able to estimate the effectiveness of various sanitisers as a function of type, concentration and exposure time. Finally, L. monocytogenes growth in the products down the supply chain should be estimated by using realistic time-temperature trajectories, and validated microbial kinetic parameters, both of them currently available in the literature.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

The current treatment for cervico-facial cancer involves radio and/or chemotherapy. Unfortunately, cancer therapies can lead to local and systemic complications such as mucositis, which is the most common dose-dependent complication in the oral cavity and gastrointestinal tract. Mucositis can cause a considerably reduced quality of life in cancer patients already suffering from physical and psychological exhaustion. However, melatonin, whose role in the treatment of mucositis has recently been investigated, offers an effective alternative therapy in the prevention and/or management of radio and/or chemotherapy-induced mucositis. This review focuses on the pathobiology and management of mucositis in order to improve the quality of cancer patients’ lives.

The accumulation of brown algae from the genus Sargassum has been increasing over the years in coastal regions of the Caribbean, Africa, Brazil, and Mexico. This causes harmful effects to the ecosystem, health, economy, and climate due to gas emissions from its decomposition process. There is the possibility of this biomass being reused in civil construction, and few studies have been carried out on its application to common Portland cement mortar. As such, the objective of this study is to evaluate the potential of sargassum ash as a mineral addition to partial replacement of fine aggregates in Portland cement mortar. Characterizations of the raw materials were carried out through X-ray fluorescence spectroscopy, loss on ignition, particle size distribution, Brunauer–Emmett–Teller (BET), real density, X-ray diffraction, scanning electron microscopy, and dispersion spectroscopy of electrons. The mortars were prepared by partially replacing the fine aggregate (sand) with sargassum ash, at 0%, 5%, 10% and 20%. Mortar performance was evaluated through water absorption, apparent porosity, apparent specific mass, compressive strength after 7, 28, and 63 days after curing. Lastly, a life cycle assessment in accordance with ISO standards 14040:2006 and 14044:2006. The results showed that replacing sand with sargassum ash increases water absorption, apparent porosity, and decreases the apparent specific mass and compressive strength as replacement increases. Nevertheless, the compressive strength results after 63 days, for 5 and 10% replacement did not differ statistically from reference values. The life cycle assessment indicates that mortars with partial replacement of sand by sargassum ash showed positive environmental impacts when compared to reference values for most categories regardless of the scenario analyzed, especially for mortar with 10% replacement. As such, the use of sargassum ash at 10% does not alter compressive strength values after 63 days while reducing its environmental impact. The application of this biomass in civil construction materials provides a destination for this algae that has been causing several social, environmental, and economic problems.

The world is currently experiencing the fourth industrial revolution driven by the newest wave of digitisation in the manufacturing sector. The term Industry 4.0 (I4.0) represents at the same time: a paradigm shift in industrial production, a generic designation for sets of strategic initiatives to boost national industries, a technical term to relate to new emerging business assets, processes and services, and a brand to mark a very particular historical and social period. I4.0 is also referred to as Industrie 4.0 the New Industrial France, the Industrial Internet, the Fourth Industrial Revolution and the digital economy. These terms are used interchangeably in this text. The aim of this article is to discuss major developments in this space in relation to the integration of new developments of IoT and cyber physical systems in the digital economy, to better understand cyber risks and economic value and risk impact. The objective of the paper is to map the current evolution and its associated cyber risks for the digital economy sector and to discuss the future developments in the Industrial Internet of Things and Industry 4.0.

There are important challenges for modeling large electrical distribution circuits, even more with the presence of distributed renewable generation. Constructing simulations for assessing the effect of the penetration of distributed generation on electrical distribution networks has become of great importance for Distribution Network Operators (DNOs). This paper proposes a simulation strategy based on open-source platforms and the integration of scripting tools for the rapid modeling of large-scale electrical distribution circuits with distributed renewable generation. The implementation is based on the adaptation of a tool called QGIS2OpenDSS, which creates OpenDSS distribution network models directly from an open-source geographic information system, QGIS. The plugin’s capabilities are demonstrated using a real distribution feeder with more than 60% penetration of renewable generation based on photovoltaic systems. These simulations are carried out using real data from a circuit provided by a DNO in the Dominican Republic, which is used to demonstrate how this approach provides a more accessible and flexible way to simulate and assess the effect of Distributed Energy Resources (DERs) in Medium Voltage (MV) and Low Voltage (LV) networks, enabling utilities to evaluate system performance and identify potential issues.

Members of the genus Armillaria are widespread forest pathogens against which effective protection has not yet been developed. Due to their longevity and the creation of large-scale cloning of Armillaria individuals, the use of mycoviruses as biocontrol agents (BCAs) against these pathogens could be an effective alternative. This work describes the screening of double-stranded RNA banding patterns as a first approach for potential virus discovery and the use of stranded total RNA-seq for viral detection and characterization in Armillaria spp. collected in the Czech Republic. A total of five single-stranded RNA viruses were detected in Armillaria ostoyae and A. cepistipes, including the first virus of the family Tymoviridae found infecting a member the genus Armillaria and four viruses belonging to the recently described virus group "ambiviruses" with circular ambisense genome organization. Both hammerhead (HHRz) and hairpin (HpRz) ribozymes were detected in all the ambiviricot sequences. Armillaria viruses were compared by phylogenetic analysis and confirmed their specific host by direct RT-PCR, which showed the occurrence of interspecies transmission.

The analysis and simulation of water quality in distribution networks is a complex issue of great concern today. The analysis of the evolution of water age, as a simple indicator of water quality in the network, is of great interest in both design and operation phases. Understanding the factors that have the strongest influence on water quality is key to developing adequate strategies aimed at preserving it. This paper firstly analyses the factors with biggest influence in the tanks water age, to support the selection of the most appropriate configuration from the point of view of water quality during design phases. Then, the main considerations when modelling tanks following the different mixing models considered in Epanet have been presented. Also, a real tank behaviour has been characterised through field measurements and Epanet simulations in order to determine the best fitted mixing model.

Nanocrystalline silicon oxide (nc-SiOx:H) is a multipurpose material with its varied application in solar cells as a transparent front contact, intermediate reflector, back reflector layer and even tunnel layer for passivating contacts, owing to easy tailoring of its optical properties. In this work, we systematically investigate the influence of gas mixture (SiH4, CO2, PH3 and H2), RF power and process pressure on the optical, structural and passivation properties of thin n-type nc-SiOx:H films prepared in an industrial, high throughput, plasma-enhanced chemical vapor deposition (PECVD) reactor. We provide a detailed description of the n-type nc-SiOx:H material develop-ment using various characterization techniques (SEM, EDX, Raman spectroscopy, and spectro-scopic ellipsometry) with a focus on the relationship between the material properties and the pas-sivation they provide to n-type c-Si wafers characterized by their effective carrier lifetime (τeff). Further, we also outline the parameters to be kept in mind while developing different n-type nc-SiOx:H layers for different solar cell applications. We report a tunable optical gap (1.8 – 2.3 eV) for our n-type nc-SiOx:H films as well as excellent passivation properties with τeff up to 3.5 ms (iVoc ~ 715 mV) before annealing. Oxygen content plays an important role in determining the crystallinity and hence passivation quality of the deposited nanocrystalline silicon oxide films.

The mechanisms underlying the establishment of asymmetric structures during development remain elusive. The wing of Drosophila is asymmetric along the Anterior-Posterior (AP) axis, despite that its growth signals that drive its growth are presumably symmetric. Here, we investigated the contribution of cell recruitment, a process that drives wing fate differentiation in Drosophila, to the asymmetric shape and pattern of the adult wing. Genetic impairment of cell recruitment results in a significant reduction in adult wing asymmetry, primarily affecting the region between longitudinal vein 5 and the wing margin (L5-M). Morphometric analysis reveals that the lack of cell recruitment results in a more symmetric wing with respect to the AP, suggesting a contribution of cell recruitment to the establishment of asymmetry in the adult wing. A close examination of the expression of the wing selector gene vestigial (vg) in wing disc does not support this hypothesis. However, the circularity of the Vg pattern significantly increase in recruitment-impaired wing disc, suggesting that while the decrease of the L5-M region in the adult wing may not be attributed to cell recruitment, it could contribute to the overall asymmetry of the adult wing. We conclude that cell recruitment, a widespread mechanism that participates in growth and patterning of several developing systems, could drive, at least partially, the asymmetric shape of the Drosophila wing.

The term Conjugated Linoleic Acid (CLA) refers generically to a class of positional and geometric conjugated dienoic isomers of linoleic acid. Among the isomers of linoleic acid cis9, trans11-CLA (c9, t11-CLA) and trans10, cis12-CLA (t10, c12-CLA) are found to be bio-logically active isomers, and they occur naturally in milk, dairy products and meat from ruminants. In addition, some vegetables and some sea-foods have also been reported to contain CLA. Although the CLA levels in these natural sources are insufficient to confer the essential health benefits, anti-carcinogenic or anti-cancer effects are of current interest. In the rumen, CLA is an intermediate of isomerization and the biohydrogenation process of linoleic acid to stearic acid conducted by ruminal microorganisms. In addition to rumen bacteria, some other bacteria, such as Propionibacterium, Bifidobacterium and some lactic acid bacteria (LAB) are also capable of producing CLA. In this regard, Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) has demon-strated the ability to produce CLA isomers from linoleic acid by multiple enzymatic activi-ties, including hydration, dehydration, and isomerization. L. plantarum is one of the most versatile species of LAB and the bacterium is widely used in the food industry as a micro-bial food culture. The studies reviewed in this article reveal how, in the production of some fermented foods, the use of appropriate strains of L. plantarum, as a starter or additional culture, can be considered a critical factor in the design of new CLA-enriched functional foods.

Malnutrition problems are related to diets that lack one or more essential elements, which it is extremely important to food enrichment to improve the content of compounds effective for health. The objective of this study is to evaluate the effect of the addition of Ca2+, K+ and Mg2+ on the induction of nutraceutical quality in grafted tomatoes grown in the NFT (Nutrient Film Technique) system. In the experiment, two factors were evaluated: plants with and without grafting and the foliar application of 10 ml L−1 Ca2+, 4 ml L−1 K+ and 10 ml L−1 Mg2+ cations separately for each case, in addition to the control. The treatments were evaluated using a completely randomized design, with 5 repetitions per treatment. The interactive effects between grafting and foliar application of Ca2+ induced a greater content lycopene, β-carotene and total flavonoids in fruits of tomato. The interactive effects between the graft and the Mg2+ foliar applications obtained the best results in the phenol content. As regards, capacity DPPH and ABTS, the graft decreased concentration, increasing the content of these through foliar applications of calcium. Regarding the enzymatic variables, graft factor increased activity catalase, glutathione peroxidase and phenylalanine ammonium lyase, obtained the best results graft interaction and foliar application of calcium and magnesium. The results obtained demonstrate the influence of the use of grafts and foliar applications of cal-cium and magnesium as tools that could improve the nutraceutical quality content of tomato crop

Functional articular cartilage regeneration remains an unmet medical challenge, increasing the interest for innovative biomaterial-based tissue engineering (TE) strategies. Hydrogels, 3D macromolecular networks with hydrophilic groups, present articular cartilage-like features such as high water content and load-bearing capacity. In this study, 3D porous polyethylene glycol diacrylate (PEGDA) hydrogels were fabricated combining the gas foaming technique and an UV-based crosslinking strategy. The 3D porous PEGDA hydrogels were characterized in terms of their physical, structural and mechanical properties. Our results showed that the size of the hydrogels pores can be modulated by varying the initiator concentration. In vitro cytotoxicity tests showed that 3D porous PEGDA hydrogels presented high biocompatibility both with human chondrocytes and osteoblast-like cells. Importantly, the 3D porous PEGDA hydrogels supported the viability and chondrogenic differentiation of human bone marrow-derived mesenchymal stem/stromal cells (hBM-MSCs)-based spheroids as demonstrated by the positive staining of typical cartilage extracellular matrix (ECM) (glycosaminoglycans (GAGs)) and upregulation of chondrogenesis marker genes. Overall, the produced 3D porous PEGDA hydrogels presented cartilage-like mechanical properties and supported MSC-spheroid chondrogenesis, highlighting their potential as suitable scaffolds for cartilage TE or disease modelling strategies.

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

The wave energy converter (WEC) technology constantly develops new designs and models. To encourage its development within the energy sector, research is required to improve current designs and create durable and effective devices. However, it is also crucial to investigate the suitability of a WEC to a site-specific sea condition as this can impact its optimal power absorption and constructability. This study evaluates and compares the efficiency of a heaving buoy with varied geometries in one of the most energetic places along the Mexican coast. A statistical analysis of the wave climate on the coast of Ensenada during the last 42 years is performed to define the conditions to which the device is subjected. The location of the WEC in shallow waters is chosen using a computational model which solves the modified mild slope equation in its elliptic shape. The heaving buoy floater is studied using three distinct geometries: a semi-sphere, a cylinder, and a proposed rounded semi-rectangle. The hydrodynamic response of the three geometries is then analysed in the frequency and time domain using ANSYS AQWA. The hydrodynamic study involves the assessment of the floating body dynamics, exerted forces, the power absorbed as well as the suitability of the proposed power take-off (PTO) system. Findings reveal that the proposed geometry absorbs the most energy, with an annual power of 135.11 MW, and that the transmission PTO design is appropriate for this type of technology.

In this paper, four probability functions are compared with the purpose of establishing a methodology to improve the accuracy of the estimated wind energy in a desert city in northwestern Mexico. For the statistical modeling, 3 time series of wind speed data were used, corresponding to the years 2017, 2018, and 2019, recorded with a sonic anemometer at a sampling frequency of 10 Hz. From these, the analysis is performed with different stationarity periods (5, 30, 60, and 600 seconds). The estimation of the parameters characterizing the probability density functions was performed using different methods; the statistical models were evaluated by the coefficient of determination and the Nash-Sutcliffe efficiency coefficient, while their accuracy by the measured quadratic error, the mean square error, the mean absolute error, and the mean absolute percentage error. It was found that Weibull with the energy pattern factor method and Gamma using the method of moments were the probability density functions that best describe the statistical behavior of the wind speed and, therefore, better estimate the energy generated, so it is concluded that the proposed methodology will allow having greater confidence, both in the estimation of the wind speed and in the small wind energy available for its use.

Polyelectrolyte-drug complexes are interesting alternatives to improve unfavourable drugs properties. Vancomycin (VAN) is an antimicrobial used in the treatment of methicillin-resistant Staphylococcus aureus pulmonary infections in patients with cystic fibrosis. It is generally administered intravenously with high incidence of adverse side effects, which could be reduced by intrapulmonary administration. Currently, there are no commercially available inhalable formulations containing VAN. Thus, the present work focuses on the preparation and characterization of an ionic complex between hyaluronic acid (HA) and VAN with potential use as inhalable formulations. Particulate-solid HA-VAN25 complex by spray drying from an aqueous dispersion was obtained. FTIR spectroscopy and thermal analysis confirmed the ionic interaction between HA and VAN, while an amorphous diffraction pattern by X-ray was observed. The powder density, geometric size and morphology showed a suitable aerosolization and aerodynamic performance of the powder, indicating the capability of reaching the deep lung. An in vitro extended-release profile of VAN from the complex was obtained, exceeding 24 hours. Microbiological assays against methicillin-resistant and -sensitive reference strains of Staphylococcus aureus, showed that VAN preserves its antibacterial efficacy. In conclusion, HA-VAN25 exhibited interesting properties for the development of inhalable formulations with potential efficacy and safety advantages over conventional treatment.

Despite the global richness of food plants, only a small portion is used as food for humans. Although most wild food plants (WFPs) are underutilized as food, they can contribute to food security and biocultural conservation through sustainable management. The goal of this research was to identify the best terminological presentation of a novel food product and to understand the influences of the expectations on products with WFP. This research was conducted using an online questionnaire with a final national sample of 724 people. The participants answered questions about their socioeconomic profile, food neophobia, prior knowledge, and expectations regarding the taste and appropriateness of native fruit juices. The questions were randomized so that a person would not receive the same picture or product name more than once. The results show that taste expectancy decreases in relation to products associated with WFP names and forest environments. Food neophobia is the variable that influences expectations the most. To ensure biocultural conservation and cultural valuation, WFP popularization programs should maintain the original (popular) name of the species. However, to help more distant consumers develop familiarity, the flavor, shape, color, or texture of these products can be associated with those of conventional plants.

This analytical cross-sectional study was designed to evaluate the association between glycemic control and peripheral arterial disease in patients with diabetic foot with more than ten years of evolution of diabetes mellitus who attended the diabetic foot outpatient clinic of the Guillermo Almenara National Hospital between June 2015 and February 2017. Glycosylated hemoglobin (HbA1C) and ankle-brachial index (ABI) were used to diagnose glycemic control and peripheral arterial disease, respectively. A generalized Poisson log-linear regression model was used to calculate the crude (cPR) and adjusted (aPR) prevalence ratios, with 95% confidence intervals, and a significance level of p < 0.05. 226 patients were included in the study, finding 23% (n=52) with good glycemic control, and 44.7% (n=101) with peripheral arterial disease. The adjusted model found statistically significant associations for glycemic control, age, and sedentary lifestyle with peripheral arterial disease. Compared with patients with good glycemic control, those with poor glycemic control had a 34% higher probability of presenting peripheral arterial disease (aPR: 1.34, 95%CI: 1.01-1.79, p=0.045). The prevalence of good glycemic control in the population with diabetic foot is low. Poor glycemic control was found to be independently associated with the presence of peripheral arterial disease.

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

There have been beaching events of the marine alga pelagic sargassum in coastal regions of the Caribbean Sea, West African countries, and the north-northeast region of Brazil since 2011. Its presence has caused environmental and socioeconomic impacts while several studies were conducted in order to understand the causes of this phenomenon, as well as alternatives to mitigate its impacts. The objective of this research was to evaluate pelagic sargassum biomass as a raw material for the manufacture of medium-density multilayer particleboards. These are composed of 30% sargassum particles in their inner layer and 70% sugarcane bagasse particles on their outer layers which are bonded with castor oil-based polyurethane resin. A physical and chemical characterization was carried out in order to evaluate sargassum particles while physical and mechanical tests were carried out in order to evaluate the panels. Results were subsequently compared with indications from NBR 14810-2:2018 and ISO 16893:2016 standards. A life cycle assessment based on ISO 14040:2006 and 14044:2006 was carried out as to complement the feasibility study of these panels and to compare their different manufacturing processes. The multilayer panels met the minimum requirements for physical and mechanical properties established by regulations, indicating that the Sargassum spp. biomass can be used as filling. The life cycle assessment study indicates that sargassum panels produced in the Belém-PA-Brazil region present lower environmental impacts in four of seven evaluated categories when compared to conventional panels. As such, they constitute an alternative way to mitigate environmental impacts generated by beaching events.

Ammonia can be considered a relevant compound in the future energy sector, playing a significant role as an energy carrier, storage, or carbon-free fuel. However, the production of this molecule has a high energy demand, and the use of natural gas, which is not free of controversy due to the accidental leakage into the atmosphere produced during extraction and the fact that it is a non-renewable source, contributes to increasing greenhouse gas emissions. Reducing the process’s energy demand and carbon footprint will be essential to making ammonia a clear alternative for a carbon-free economy. Given the vast experience in ammonia production and handling, this gas seems to be the logical step forward in the evolution of the energy sector. However, the current uncertainty in the global market requires cautiousness in decision-making. Several factors may impact economic growth and human welfare, thus needing a careful assessment before taking any transcendental decisions that could affect worldwide energy prices and raw material availability.

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

Turner syndrome (TS) is caused by a complete or partial absence of an X or Y chromosome, including chromosomal mosaicism, affecting 1 in 2,500 female live births. Sister chromatid exchange (SCE) is used as a sensitive indicator of spontaneous chromosome instability. Cells from mosaic patients constitute useful material for SCE evaluations as they grow under the influence of the same genetic background and endogenous and exogenous factors. We evaluated proliferation dynamics and SCE frequencies of 45,X and 46,XN cells of 17 mosaic TS patients. In two participants, 45,X cells exhibited a proliferative disadvantage in relation to 46,XN cells after 72h of cultivation. The analysis of mean PI showed significant differences between 45,X and 46,XN lineages; however there were no intraindividual differences. On the other hand, mean SCE frequencies showed no differences between the two lineages, but there were intraindividual differences in 5 patients. The absence of mean SCE frequency differences between 45,X and 46,XN lineages may indicate that both were equally unstable, as more than 70% of the 46,XN lineages had an anomalous karyotype. However, 46,XN had a higher mean PI, suggesting that the amount of cells with a karyotype distinct from 45,X may increase with time in mosaic TS women.

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.

In voice analysis, the electroglottographic (EGG) signal has long been recognized as a useful complement to the acoustic signal, if only when the vocal folds are actually contacting, such that this signal has an appreciable amplitude. However, phonation can occur also without vocal fold contacting, as in breathy voice, in which case the EGG amplitude is low, but not zero. It is of great interest to identify the transition from non-contacting to contacting, because this will substantially change the nature of the vocal fold oscillations; yet that transition is not in itself audible. The magnitude of the normalized peak derivative of the EGG signal is a convenient indicator of contacting, but no current EGG hardware has a sufficient signal-to-noise ratio of the derivative. The textbook techniques of spectral thresholding and static notch filtering are straightforward to implement, can run in real time, and can mitigate several noise problems in EGG hardware.

Recently quantum cosmology in tomographic representation was considered. as an important tool to analyze the quantum states of the early universe in relation with the subsequent classical evolution. Given a wave function the correspondent tomogram is defined proportional to the square modulus of its fractional Fourier transform. The classical limit obtained by taking the limit ℏ→0 can be compared with the classical tomogram obtained from the classical hamiltonian formalism. In this paper we show that a set of tomograms can be derived as exact solutions of a third order equation when a de Sitter quantum universe is considered. We finally discuss the limits of this approach to quantum cosmology because the extension to equations with arbitrary potentials can become extremely complicated for potentials given by algebraic polynomials of degree greater than two and therefore also for potentials expressible by arbitrary functions.

Despite advances in algorithms and computational platforms, de-novo genome assembly remains a challenging process. Due to the constant innovation in sequencing technologies (Sanger, SOLiD, Illumina, 454, PacBio and Oxford Nanopore), genome assembly has evolved to respond to the changes in input data type. This paper includes a broad and comparative review of the most recent short-read, long-read and hybrid assembly techniques. In this review, we provide (1) an algorithmic description of the important processes in the workflow that introduces fundamental concepts and improvements; (2) a review of existing software that explains possible options for genome assembly; and (3) a comparison of the accuracy and the performance of existing methods executed on the same computer using the same processing capabilities and using the same set of real and synthetic datasets. Such evaluation allows a fair and precise comparison of accuracy in all aspects. As a result, this paper identifies both the strengths and weaknesses of each method. This comparative review is unique in providing a detailed comparison of a broad spectrum of cutting-edge algorithms and methods.

Ideas about Artificial Intelligence appeared about half a century ago, but only now is it becoming an essential element of everyday life. The data provided is getting bigger and bigger and, in this case, we need artificial intelligence that helps us with superhuman powers. The interaction with medicine is getting closer and closer, medicine being a field that continues to be perfected. Machine learning, deep learning, neural networks, computer vision are some of the mechanisms that are already applied in medicine, becoming a trend in healthcare worldwide. Artificial intelligence will be the thing that will change contemporary medicine. Developed countries such as Japan, France, Germany have already implemented artificial intelligence in their medical systems. The help is in medical diagnosis, patient monitoring, personalized therapy, and workflow optimization. Artificial intelligence will help surgeons to perfect their skills, to standardize techniques, to choose the best surgical technique. The goal is to predict complications, reduce diagnostic time, diagnose complex pathologies, guide the surgeon intraoperatively and reduce medical errors. We are at the beginning but the potential is enormous.

Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.

This paper is focused on mapping the current evolution of Internet of Things (IoT) and its associated cyber risks for the Industry 4.0 (I4.0) sector. We report the results of a qualitative empirical study that correlates academic literature with 14 - I4.0 frameworks and initiatives. We apply the grounded theory approach to synthesise the findings from our literature review, to compare the cyber security frameworks and cyber security quantitative impact assessment models, with the world leading I4.0 technological trends. From the findings, we build a new impact assessment model of IoT cyber risk in Industry 4.0. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of economics impact assessment models for I4.0.

A single water pollution by dyes is a huge environmental problem; there is a necessity to produce new decolorization methods that are effective, cost-attractive, and suitable in industrial use. Magnetic chitosan polymers offer the advantage of easy separation from the dye solution. In this work, a Chitosan-Fe polymer was synthesized, characterized, and tested for removal of the azo dye Direct Red 83:1 from water. The polymer was characterized in terms of surface morphology (SEM), elemental analysis (EA), differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), infrared spectrophotometry (IR), X-ray powder diffraction (XRD) and density functional theory (DFT). The reported results hint that 1 g and pH 7.0 were the best conditions to carry out both kinetic and isotherm models. To understand the adsorption behavior of Direct Red 83:1 onto the polymers, adsorption rate and maximum adsorption capacity were calculated using kinetic tests and isotherm curves respectively. The kinetic data and mechanism of the adsorption process were analyzed by three models and the equilibrium data by three adsorption isotherms. The results indicated that the adsorption process follows a pseudo-second-order kinetics (R2= 0.999) and fits the Temkin isotherm (R2= 0.946), indicating that the adsorption occurred on heterogeneous surfaces. The newly synthesized Chitosan-Fe polymer exhibited good adsorption properties and easy separation of cleaned water.

Epigenetic mechanisms, including post-translational modifications of DNA and histones that influence chromatin structure, regulate gene expression during normal development, and are also involved in carcinogenesis and cancer progression. The histone methyltransferase G9a (euchromatic histone lysine methyltransferase 2, EHMT2), which mostly mediates mono- and dimethylation by histone H3 lysine 9 (H3K9), influences gene expression involved in embryonic development and tissue differentiation. Overexpression of G9a has been observed in several cancer types, and different classes of G9a inhibitors have been developed as potential anticancer agents. Here, we review the emerging evidence suggesting the involvement of changes in G9a activity in brain tumors, namely glioblastoma (GBM), the main type of primary malignant brain cancer in adults, and medulloblastoma (MB), the most common type of malignant brain cancer in children. We also discuss the role of G9a in neuroblastoma (NB) and the drug development of G9a inhibitors.

The aim of this work is to compare two softwares (MAUD and TOPAS) based on the Rietveld algorithm and to test the concept of tolerance factor using the dissolution at high temperature of yttrium into BaTiO₃. In general, both softwares give up different values of the crystalline parameters however the trends are similar in most cases but the analysis of the strain and crystallite size in the BaTiO₃ crystals suggests that, in this particular case, MAUD offered results more consistent with the expected behavior. Using the crystalline parameters calculated by Rietveld, the tolerance factor values were obtained and these data suggest even better stability in the crystalline structure than that expected using theoretical parameters. Tolerance factor concept also indicates that Ti⁴⁺ should be preferred.

In recent years, intensive work has been carried out to achieve maximum energy production in photovoltaic power plants. Today, this challenge has to be solved for arrays of solar panels that move with the object on which they are installed (vehicles, trucks, ships, etc.). The present work tries to find the best solution for both constant voltage systems and for cases of maximum intensity. Once found, these solutions will be applied in real time for the dynamic recharging of battery packs, trying to achieve energetically autonomous vehicles.To solve these situations, a new computational method of voltage and amperage calculation has been developed in this paper, based on Dijkstra’s minimum path finding algorithm on graph theory, adapted to electrical circuits. For this purpose, panel performance analysis sensors, developed at the University of Malaga, have been combined with different electronic solutions (wifi relay devices using esp8266 or similar chips) achieving an accurate and sufficiently fast solution at very low cost. With this, series or parallel configurations can be carried out depending on the type of energy generation sought. The theoretical solutions using Minkowski paths, achieved in the past, have been simulated and subsequently constructed in this article, indicating the diagrams necessary for their realisation.

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

B chromosomes (B) are supernumerary elements found in many taxonomic groups. Most B chromosomes are rich in heterochromatin and composed of abundant repetitive sequences, especially transposable elements (TEs). Bs origin is generally linked to the A chromosome complement (A). The first report of a B chromosome in African cichlids was on Astatotilapia latifasciata, which can harbor 0, 1 or 2 B chromosomes. Classical cytogenetics studies found high TE content on the species B chromosome. In this study, we aim to understand TE composition and expression on A. latifasciata genome and its relation to the B chromosome. We use bioinformatics analysis to explore TEs genome organization and also their composition on the B chromosome. Bioinformatics findings were validated by fluorescent in situ hybridization (FISH) and real-time PCR (qPCR). A. latifasciata has a TE content similar to other cichlid fishes and several expanded elements on its B chromosome. With RNA sequencing data (RNA-seq) we showed that all major TE classes are transcribed in brain, muscle and male/female gonads. The evaluation of TE expression between B- and B+ individuals showed that few elements have differential expression among groups and expanded B elements were not highly transcribed. Putative silencing mechanisms may the acting on the B chromosome of A. latifasciata to prevent adverse consequences of repeat transcription and mobilization in the genome.

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing distance away from the Madre de Dios headwaters (as the crow flies), did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

The soil-structure interaction represents an important parameter when analyzing the dynamic behavior of bridges, taking into account the integration between soil, foundation, and structure to ensure an adequate structural representation. In this paper, a computational modeling strategy using soil-structure interaction (SSI) methodology was applied to represent the dynamic behavior of a pedestrian bridge (LOP). The computational models were validated using monitoring results from an extensive structural health monitoring campaign. The bridge monitoring program was characterized using embedded sensors and cutting-edge technology for remote monitoring: ground-based radar interferometry and video motion amplification. The instrumentation results were compared to establish the capabilities and advantages of this novel remote monitoring technique. The experimental results obtained from free and forced vibrations in the asset served as a basis for validating the developed computational model and allowed evaluating the asset be-havior in service for different loading conditions. This paper emphasizes the SSI approach to represent the pedestrian bridge dynamic behavior more accurately, allowing computational models to represent the LOP structural responses over the course of its life-cycle.