Landscapes evolve due to climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics. These processes link geological processes at depth to surface features. Consequently, the study of landscapes can reveal essential information about the geochemical footprint of ore deposits at depth. Advances in satellite imaging and computing power have enabled the creation of large geospatial datasets, the sheer size of which necessitates automated processing. We describe a methodology to enable the automated mapping of landscape pattern domains using machine learning (ML) algorithms. From a freely available Digital Elevation Model, derived data, and sample landclass boundaries provided by domain experts, our algorithm produces a dense map of the model region in Western Australia. Both random forest and support vector machine classification achieve about 98\% classification accuracy with reasonable runtime of 48 minutes on a single core. We discuss computational resources and study the effect of grid resolution. Larger tiles result in a more contiguous map, while smaller tiles result in a more detailed, and at some point, noisy map. Diversity and distribution of landscapes mapped in this study support previous results. In addition, our results are consistent with the geological trends and main basement features in the region.

Voice cloning, an emerging field in the speech processing area, aims to generate synthetic utterances that closely resemble the voices of specific individuals. In this study, we investigate the impact of various techniques on improving the quality of voice cloning, specifically focusing on a low-quality dataset. To contrast our findings, we also use two high-quality corpora for comparative analysis. We conduct exhaustive evaluations of the quality of the gathered corpora in order to select the most suitable audios for the training of a Voice Cloning system. Following these measurements, we conduct a series of ablations by removing audios with lower SNR and higher variability in utterance speed from the corpora in order to decrease their heterogeneity. Furthermore, we introduce a novel algorithm that calculates the fraction of aligned input characters by exploiting the attention matrix of the Tacotron 2 Text-to-Speech (TTS) system. This algorithm provides a valuable metric for evaluating the alignment quality during the voice cloning process. We present the results of our experiments, demonstrating that the performed ablations significantly increase the quality of synthesised audios for the challenging low-quality corpus. Notably, our findings indicate that models trained on a 3-hour corpus from a pre-trained model exhibit comparable audio quality to models trained from scratch using significantly larger amounts of data.

In the present study the synthesis of gold nanoparticles (AuNPs) loaded with methotrexate (MTX) has been carried out in order to obtain controlled size and monodispersed nanocarriers, around 20nm. Characterization study shows metallic AuNPs with MTX polydispersed on the surface. MTX is linked by a replacement of citrate by the MTX carboxyl group. The drug release profiles showed faster MTX release when it is conjugated, which leads to the best control of plasma concentration. Also, the enhanced release observed at pH 5 could take advantage of the pH gradients that exist in tumor microenvironments to achieve high local drug concentrations. AuNPs-MTX conjugates were tested by flow cytometry against lung (A-549) and colon (HTC-116) cancer cell lines. Results for A-549 showed a lighter dose-response effect than for colon cancer ones. This could be related to the presence of folate receptors in line HTC-116 on the contrary than line A-549, supporting the specific uptake of folate-conjugated AuNPs-MTX by folate receptor positive tumor cells. Conjugates exhibited considerably higher cytotoxic effects compared with the effects of equal doses of free MTX. Anexin V-PI test sustain as cell death mechanism apoptosis, which is normally disabled in cancer cells.

The use of sustainable energy sources is a feasible alternative for fossil fuel products, which can represent a positive factor to alleviate many current environmental issues. In that sense, not only the sustainable industrial development is important, but also sustainable practices at local level, including households. Specifically, heating and cooking are one of the most important activities that require energy in households, where the role of biomass could be interesting, as it can provide an energy source with lower environmental impact. However, there is room for improvement in biomass stoves, whose adaptability to specific wastes, as well as their improvement in efficiency, should be accomplished. The aim of this work was to assess the improvement of combustion performance of a domestic stove by the implementation of a programmable logic converter for a better adaptation to different biomass samples (holm oak, pear tree, poplar and sugarcane bagasse pellets). Thus, the working regime of the stove was controlled, especially concerning the screw conveyor (to regulate pellet feeding) and flue gas fan (to change oxygen supply). As a result, better combustion performances were obtained, heat capacities from 5.66 to 8.67 kW for the selected samples. On the other hand, different improvements of the combustion stove to avoid blockages, for instance, are proposed as further steps.

Keywords: glycerin; Ni-based catalyst; lanthanum; semi-industrial scale; hydrogen production; biorefinery; monitoring.

Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the concept of Digital Twin (DT) and the interest of its application in photovoltaic installations. A comparison is made on how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, the energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It is reviewed how, by providing real-time data and analysis, DTs enable more informed decisions in the solar energy sector. The objectives of the review are to study the digital twin technology and to analyze its application and implementation in photovoltaic systems.

We conducted this systematic review with the objective to understand the efficacy and safety of proton pump inhibitors [PPIs] in the pediatric population. We have used PubMed to identify randomized controlled trials [RCTs] published between 1st June 2010 and 30th June 2023, in patients from birth to 18 years old, with gastroesophageal reflux disease [GERD], who received treatment with any PPI. The literature yielded 76 articles and 13 met inclusion criteria. For infants, PPIs were equal to placebo in reducing GERD symptoms in 4 articles. In 1, the number of GER episodes and esophageal acid exposure were lower in infants who received PPIs and left lateral position, but there was no significant improvement in symptoms. In another publication, the combination of PPIs and feeding modifications [FM] was not more effective than PPIs alone. For children and adolescents, PPIs were effective in improving symptoms and achieving mucosal and histological healing, which was subsequently maintained. To conclude, PPIs are not effective to reduce symptoms related to GERD in infants, but are effective in older children, along with histological remission. Generally, PPIs are well tolerated, but it is important to not forget the possible adverse events [AE], especially if they are used for a long time.

Infant obesity has become one of the most serious global health challenges of our time. The combined prevalence of overweight and obesity has rapidly increased worldwide during the last two decades, especially in some developing countries where obesity is reaching levels on a par with some industrialized countries, or even higher. This fast growth has occurred especially in countries in the midst of rapid social-economic transitions. Most international comparisons focus on the adult population while analyses focusing on the child population are more limited. Using the methodology developed by Phillips and Sul [1], this paper studies the worldwide evolution of infant body mass index (BMI), overweight and obesity prevalence for a large sample of countries during the period 1975-2016. Our results indicate that the figures for BMI or the prevalence of obesity in different countries do not converge, while the opposite is the case for overweight prevalence in children. Furthermore, there is a non-linear relationship between obesity and income or human capital, indicating that low and middle-income countries require a strong initiative for health policies targeting obesity prevention.

The life and work of Ignacio Ellacuría, S.J. is of radical vision, and revolutionary change. His dynamic life and works accompanied El Salvador and the Universidad Centroamericana through perhaps the most tumultuous years of the country’s history, yet there has been limited work done to examine his contributions. This paper shows how Ellacuría viewed the role of a Christian intellectual, and a Christian university within his philosophical and theological framework. I argue that Ignacio Ellacuría held, similarly to his soteriological views, that the intellectual must also be willing to sacrifice all for the sake of his/her work in a pattern of discipleship/martyrdom prefigured by his exemplars Christ and Socrates. It was this dedication to praxis and theory that western theology and philosophy had respectfully lost since their foundations which he sought to restore to a central role. In conclusion, the Christian intellectual and institution, according to Ellacuría, must use its voice and life in service of the people even to the point of martyrdom; he would argue, the implicit reason for Christian martyrdom and the crucifixion of Christ himself.

Global energy scenario is becoming vital for the sustainable economic development of a region or country. Current changes in energy production, mainly due to scarcity and geopolitical factors, have proven the need for changes in energy mix towards a lower energy dependence. In that sense, a considerable amount of biomass waste is generated in many regions, because of agro-industrial activities, whose management could contribute to energy production. The aim of this work was to study the determination of combustion conditions in a biomass stove by using different raw materials as fuels, such as pine, poplar, and plum tree pellets. For that purpose, power, excess air, and biomass content were optimized, among other parameters, and fumes were analyzed with a Testo 335 analyzer, recording temperatures with temperature probes. As a conclusion, high yields were found for the optimized parameters of the studied biomass (ranging from 91.1 % for poplar pellet to 92.34 % for pine pellet), making these three biomass fuels suitable for combustion in the abovementioned stove. Also, increasing biomass flow by 25 % in the stove contributed to a higher efficiency of the process, especially in the case of plum tree pellets.

Mirror Therapy (MT) and Cognitive Therapeutic Exercise (CTE) are two neurorehabilitation techniques based on neuroplasticity and designed to enhance the functionality of the upper limb. Therefore, the aim is to assess the effectiveness of the combination of CTE and MT with task-oriented training (TOT) on fine and gross motor skills of the affected hand, as well as the functionality of the affected upper limb, autonomy, independence, and quality of life (QoL) in patients with acute stroke. This longitudinal and multicenter study involved a sample of 120 participants selected randomly and consecutively. Three groups were formed, including a control group (CG) and two treatment groups, one with MT and the other with CTE. The functionality of the upper limb, fine and gross motor skills, the quantity and quality of use of the affected upper limb, autonomy, and QoL were evaluated using various scales validated in the Spanish population at the baseline, after 20 treatment sessions, and at three months of follow-up. ANCOVA analysis was conducted, revealing statistically significant differences between assessments in the CG compared to the experimental groups (GEs), indicating a notable improvement in overall functionality, fine and gross motor skills, autonomy, and QoL in the latter. However, there were no significant differences between the GEs. Therefore, the application of either of these experimental combinations is crucial for the motor recovery, functionality, and improvement of the quality of life of individuals who have suffered a stroke.

The disruption in healthcare attention to people with alcohol dependence, along with psychological decompensation consequence of lockdown derived from COVID-19 pandemic, could have a negative impact on people who suffers from alcohol abuse disorder. Retrospective observational study of 9,966 men aged ˃16 years registered as having diagnosis of alcohol abuse disorder in the electronic medical records (EMR) of the Aragon Regional Health Service (Spain). Of those who were not infected during the study period (9,576), clinical (Glutamate-oxaloacetate -GOT-, Glutamate pyruvate -GPT-, creatinine, glomerular filtration, systolic blood pressure -SBP-, diastolic blood pressure -DBP-, total cholesterol, LDL, HDL, triglycerides, and body mass index -BMI-), pharmacological (dose per inhabitant per day -DHD- of drugs used in addictive disorders, benzodiazepines and antidepressants) and health resource use variables (primary and specialized care) were considered. Student´s T-test for matched samples was performed. After carrying out the Levene´s test, the Student´s T-test was used to analyze the changes in clinical variables between alcohol abuse disorder patients with and without COVID-19. Only creatinine and LDL show a significant but clinically irrelevant changes just after and 6 months after the end of strict lockdown. The total number of DHDs for all drugs included in the study (except for Benzodiazepines), decreased. In the same way, the use of health services by these patients also decreased. The impact of COVID-19 among this group of patients has been moderate. The reorganization of health and social services after the declaration of the state of alarm in our country, made possible the maintenance of care for this vulnerable patients.

(1) Background: the use of force by Public and Private Security Forces is currently an issue of great relevance because of the potential injuries that any excessive use of force by either the active or passive subjects or a deficit in the real mastery of the appropriate Physical Intervention Techniques (PIT) may cause. For this reason, certain traditionally used Physical Intervention Techniques have been questioned by scientific research studies and punished by justice. On the other hand, certain media have dealt with this matter in a biased and unfair manner by broadcasting videos where the use of force by police officer is displayed out of context. As a consequence, this problem has been brought under the spotlight, causing general uneasiness of the communities and rapidly spreading over social networks while favoring all sorts of parallel judgments. (2) Research method: A suit equipped with 19 Inertial Measurement Units (IMU) and a Biomechanics of Bodies software application for the Marras’ analysis of the data collected on trajectory, trunk twisting velocity, its sagittal angle, load, nature and severity of the injuries associated to the different intervention techniques that have been examined. (3) Results: according to the data registered, the implementation of Operational Tactical Procedures (OTP) reduces the probability of injuries and leads to a more satisfactory outcome. (4) Conclusions: the implementation of Operational Tactical Procedures, to-gether with the awareness on the risks associated to the excessive use of force by Public and Private Security Forces and Bodies, could reduce the risk of injuries suffered by both officers and citizens.

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

It is well known that working PV plants show several maintenance needs due to wiring and modules degradation, mismatches, dust and PV cells defects and faults. There are a wide range of studies that show the theoretical and some laboratory tests of how these circumstances may affect the PV production. Thus, it results mandatory to evaluate the whole PV plant performance and, then, it’s payback time, profitability and environmental impact or carbon footprint. However, very few studies include a systematic procedure to quantify and supervise the real degradation effects and faults impacts on the field. In this paper, the authors first conduct a brief review of the most frequent PV faults and degradation that can be found on real conditions operative PV Plants. Then, they propose and develop an innovative Geographic Information System application to locate and supervise them. The designed tool has been applied to either a large PV plant of 108 kWp and a small PV plant of just 9 kWp installed on a home rooftop. For the large PV plant, 24 strings of PV modules have been modelized and introduced into the GIS application and every module in the power plant has been studied including voltage, current, power, series and parallel resistance, fill factor, normalized PV curve to STC, thermography and visual analysis. For the small PV installation 3 strings of PV panels have been studied identically. It must be noticed that PV modules in this case include power optimizers. The precision of the study allows the researchers to locate and supervise up to a third part of every PV cell in the system, which are adequately georreferenciated. The developed tool allows both the researchers and the investors to increase control on the PV plant performance and conducts to a better planification of maintenance actuations and to evaluate several PV modules replacement strategies in a preventive maintenance programme. Found PV faults include hot spots, snail tracks, EVA discoloration, PV cells fractures, busbars discoloration, bubbles and Si discoloration.

For most of its history, archaeology has taken an indulgent attitude toward looting and antiquities trafficking. The primary response to these dangers has been to publish the main findings made outside of academia. As a result of this approach and the prominent role played by police techniques in investigating such crimes, investigations are primarily based on documentary research. This approach makes it harder to determine such essential factors in this field as an object’s collecting history or discovery date. This paper offers an overview of the state of the research on the fight against antiquities trafficking. It then proposes new ways of studying collecting history, drawing on research projects on the use of archaeometry to shed light on cases of looting or trafficking involving police, court, or government intervention; hence, its qualification as “forensic.” Although the current state of knowledge does not enable the presentation of novel research, we believe that researchers and interested institutions should be made aware of the advisability of using archaeometry more directly in the fight against these scourges.

This study investigates the spatial and temporal distribution of litter at 7 beach sectors in Cadiz Bay, Southwest Spain. Two ten-day surveys carried out in autumn 2022 and spring 2023 revealed a total of 4,199 and 4,634 items, respectively, with plastic being the predominant material (71.13% in autumn, 88.39% in spring). Litter quantities varied significantly among beaches, La Puntilla showing the highest abundance with 0.48 ± 0.25 items m-1 in autumn and 1.34 ± 0.61 items m-1 in spring. The lowest abundance was recorded at sector 1 of Valdelagrana beach (0.08 ± 0.06 items m-1) during autumn and at El Castillito beach (0.08 ± 0.04 items m-1) during spring. Statistical analyses did not reveal significant differences in litter quantities between autumn and spring, however high significant interaction was shown considering both season and beach lo-cation. Seasonal differences were also observed in litter composition. Litter categories increased from 90 in autumn to 107 in spring. The top 10 litter categories varied between seasons and included cigarette butts, plastic fragments and plastic packaging. Cigarette butts were principally abundant in autumn because re-lated to summer beach users and wet wipes were particularly observed in spring because linked to wastewaters and river discharges especially relevant in winter months. Hydrodynamic and wind conditions were analyzed, revealing complex relationships with litter abundance.

This paper presents new above-ground biomass (AGB) and biomass components equations for seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. Generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. Additionally, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The fitted equations accounted for on average 91, 83, 84 and 78% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of h or d²h as additional predictor in the d-only based equations systems slightly improved estimates of stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The fitted equations were used to estimate AGB stocks at stand level from a database on growing stock from 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were applied to map the AGB and carbon distributions in the study area, which yielded mean values of 129.84 Mg ha^-1 and 63.80 Mg ha^-1, respectively.

A series of polyacrylonitrile (PAN)-based block copolymers with poly(methyl methacrylate) (PMMA) as sacrificial bock were synthesized by atom transfer radical polymerization and used as precursors for the synthesis of porous carbons. The carbons enriched with O- and S-containing groups, introduced by controlled oxidation and sulphuration, respectively, were characterized by Raman spectroscopy, scanning electron microscopy, and X-ray photoelectron spectrometry, and their surface textural properties were measured by a volumetric analyzer. We observed that the presence of sulphur tends to modify the structure of the carbons, from microporous to mesoporous, while the use of copolymers with a range of molar composition PAN/PMMA between 10/90 to 47/53 allows the obtainment of carbons with different degrees of porosity. The amount of sacrificial block only affects the morphology of carbons stabilized in oxygen, inducing their nanostructuration, but has not effect on their chemical composition. We also demonstrated their suitability for separating a typical N2/CO2 post-combustion stream.

One of the challenges posed by renewable energies is the stabilization of parameters related to the quality of electrical energy. This study demonstrates the existence of a relationship between input blocks of hydropower and the variation of the fundamental frequency of the electricity grid. By mapping production data provided by Spanish Electric Network with frequency measured in the laboratory, it is shown that gradients of hydropower are correlated with frequency fluctuations for certain characteristic times. Considering hourly instances of energy input, the study compares two methods for calculating hydropower gradients (linear regression and pseudo-linear regression); and two methods for calculating local frequency extremes (the "specular inertia" method and analysis by comparison with the moving average), in order to corroborate the results.

Colorectal cancer (CRC) is one of the most common types of cancer worldwide. The KRAS mutation is present in 30-50% of CRC patients. This mutation confers resistance to treatment with anti-EGFR therapy. This article aims at proving that Computer Tomography (CT)-based Radiomics can predict the KRAS mutation in CRC patients. The piece is a retrospective study with 56 CRC patients from the Hospital of Santiago de Compostela, Spain. All patients had a confirmatory pathological analysis of the KRAS status. Radiomics features were obtained from the abdominal contrast enhancement CT (CECT), before applying any treatments. We used several classifiers, including adaboost, neural network, decision tree, support vector machine and random forest, to predict the presence or absence of KRAS mutation. The most reliable prediction was achieved using the adaboost ensemble on clinical patient data, with a kappa and accuracy of 53.7% and 76.8%, respectively. The sensitivity and specific were of 73.3% and 80.8%. Using texture descriptors, the best accuracy and kappa were 73.2% and 46%, respectively, with sensitivity and specificity of 76.7% and 69.2%, showing also a correlation between texture patterns on CT images and KRAS mutation. Radiomics could help manage CRC patients, and in the future, it could have a crucial role in diagnosing CRC patients ahead of invasive methods.

This paper introduces the novel concept of Time-Traveling Turing Machines (TTTMs) — Turing Machines with the ability to read symbols that have been explicitly sent from their future computational state. We delve into their properties and behavior, particularly emphasizing the importance of maintaining a self-consistent computational timeline. We present theorems demonstrating the universality of these machines and the challenges in achieving faster computations than traditional Turing Machines.

The knowledge of the precise anatomy and dimensions of the pulp chamber in the different teeth allows the odontologist to perform correct diagnosis, as well as treatment planning and moni-toring. The clinical practice has introduced cone-beam computed tomography (CB-CT) as a method to evaluate the morphology and dimensions of the pulp chamber. Nevertheless, micro-computed tomography (micro-CT) is regarded as the gold standard in approaching those topics. Here we have designed an algorithm that takes as input DICOM images from in vivo CB-CT of permanent molars to determine the accuracy CB-CT for evaluation of pulp chamber volume. The values were compared with those from in vivo CB-CT (rough and expert manipulated) and ex vivo micro-CT. The relative errors obtained with the volume calculated by the algorithm vs. the volume measured by micro-CT do not exceed 5.7%; also, no significant differences were found between algorithm volumes vs. manipulated CB-CT volumes while all volumes were different from those obtained with automatic CB-CT software. These data demonstrate that volume algorithm CB-CT based may be a reliable technique for evaluation of the pulp chamber volume in permanent molars and can be useful in the diagnosis of pulp diseases, as well as in the planning and monitoring of their treatments.

Turner syndrome (TS) is a chromosomal disorder that is caused by a missing or structurally ab-normal second sex chromosome. Subjects with TS are at an increased risk of developing intrauterine growth retardation, low birth weight, short stature, congenital heart diseases, infertility, obesity, dyslipidemia, hypertension, insulin resistance, type 2 diabetes mellitus, metabolic syndrome, and cardiovascular diseases (stroke and myocardial infarction). The underlying pathogenetic mechanism of TS is unknown. The assumption that X chromosome-linked gene haploinsufficiency is associated with the TS phenotype is questioned since such genes have not been identified. Thus, other pathogenic mechanisms have been suggested to explain this phenotype. Morphogenesis encompasses a series of events that includes cell division, the production of migratory precursors and their progeny, differentiation, programmed cell death, and integration into organs and systems. The precise control of the growth and differentiation of cells is essential for normal development. The cell cycle frequency and the number of proliferating cells are essential in cell growth. 45,X cells have a failure to proliferate at a normal rate, leading to a decreased cell number in a given tissue during organogenesis. A convergence of data indicates an association between a prolonged cell cycle and the phenotypical features in Turner syndrome. This review aims to examine old and new findings concerning the relationship between a prolonged cell cycle and TS phenotype. These studies reveal a diversity of phenotypic features in TS that could be explained by reduced cell proliferation. The implications of this hypothesis for our understanding of the TS phenotype and its pathogenesis are discussed. It is not surprising that 45,X monosomy leads to cellular growth pathway dysregulation with profound deleterious effects on both embryonic and later stages of development. The prolonged cell cycle could represent the beginning of the pathogenesis of TS, leading to a series of phenotypic consequences in embryonic/fetal, neonatal, pediatric, adolescence, and adulthood life.

Consumers are attracted by the increasing number of available SVOD platforms, but subscribing to all of them would be too expensive. To reduce costs, consumers could combine the use of proprietary subscriptions, non-proprietary subscriptions, and illegal streaming sites. In turn, platforms could enforce access control, a decision that could produce the desired reduction in non-proprietary subscriptions but also an undesired reduction in proprietary subscriptions. The effects of this decision and the determinants of SVOD content demand remain largely unexplored. We propose a baseline model where the SVOD content demand is driven by variety seeking, household financial situation, ethical evaluation, and social norms, as well as a change model where the subscription variation is driven by users’ trait reactance and perceived fairness of the decision. We conducted a survey on the current ways of SVOD content consumption and the responses to a hypothetical access control enforcement, with four randomized versions of the authentication mode. Results confirmed many of the proposed determinants and showed a noteworthy reduction in proprietary subscriptions due to the control enforcement but no effect due to the authentication modes. All these findings may help improve future models on SVOD content consumption and better address the difficult challenge of converting unauthorized users into authorized ones.

This study introduces an innovative optimization method to identify the optimal configuration of a sparse symmetric 2D array for applications in security, particularly multistatic imaging. Utilizing Genetic Algorithms (GA) in a sophisticated optimization process, the research focuses on achieving the most favorable antenna distribution while mitigating the common issue of secondary lobes in sparse arrays. The main objective is to determine the ideal configuration from specific design parameters, including hardware specifications such as number of radiating elements, minimum spacing, operating frequency range, and image separation distance. The study employs a cost function based on the the point spread function (PSF), the system response to a point source, with the goal of minimizing the secondary lobe levels and maximizing their separation from the main lobe. Advanced simulation algorithms based on Physical Optics (PO) are used to validate the presented methodology and results.

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.

This paper presents an approach to teacher identity heritage as result of the implementation of a research device created through Arts-based Research (ABR) methods, specifically with video elicitation and video essay used as research tools. Two main objectives were raised. The first one, to establish the real relevance of focusing performance on teacher identity. The second one, testing a new methodological proposal specifically designed for this purpose, but still useful in other contexts where heritage identity is as present as in teaching. The device, Body-camera, involves a process that allows new ways to understand the creation of identities using video to encourage the production of new meanings by visual and oral data. The participants were teachers in training during their internship period. Some notions about teachers' identity heritage were revealed, and also preserved, firstly, through personal perspectives by video elicitations and secondly, through collective perspectives by video essays. Both are video structures used in ABR which mix creative experience, memories, life experiences, relationships and links that shape the teachers’ professional identity.

Patients with advanced chronic liver disease (ACLD) or cirrhosis undergoing surgery have an increased risk of morbidity and mortality in contrast to the general population. Retrospective, observational study of ACLD patients to evaluate the predictive capacity of previous surgical risk scores in a European cohort of patients. ACLD was defined by the presence of thrombocytopenia <150.000/uL and splenomegaly; AST-to-Platelet Ratio Index >2; nodular liver edge by ultrasound; transient elastography >15 kPa and/or signs of portal hypertension. We assessed variables related to 90-day mortality and the discrimination and calibration of current surgical scores (Child-Pugh, MELD-Na, MRS, NSQIP, and VOCAL-Penn). Only patients with ACLD and major surgeries included in VOCAL-Penn were considered (n=512). The mortality rate at 90 days after surgery was 9.8%. Baseline disparities between H. Mar and VOCAL-Penn cohorts were identified. Etiology, obesity, or platelet count not were associated with mortality. The VOCAL-Penn showed the best discrimination (C-statistic90D= 0.876) and overall predictive capacity (Brier90D= 0.054) but calibration was not excellent in our cohort. VOCAL-Penn was suboptimal in patients with diabetes (C-statistic30D= 0.770), without signs of portal hypertension (C-statistic30D= 0.555), or with an abdominal wall (C-statistic30D= 0.608) or urgent (C-statistic180D= 0.692) surgeries. Our European cohort has shown a mortality rate after surgery similar to those described in American studies. However, some variables included in the VOCAL-Penn score were not associated with mortality, and VOCAL-Penn’s discriminative ability decreases in patients with diabetes, without signs of portal hypertension, and with abdominal wall or urgent surgeries. These results should be validated in larger multicenter and prospective studies.

(1) Background: A set of relevant Police Ergonomics Parameters (PEP) has been used for the assessment and prevention of occupational risks involved in Police Physical Interventions (PITs). Through this set of PEPs, a comparison has been made between 2 traditional PITs against 2 novel OTPs (Operational Tactical Procedures). (2) Method: The data have been collected by means of a motion capture suit fitted with 19 Inertial Measurement Units, IMUs. A specific and powerful software package specific for ergonomic analysis has been used to manage the large amount of data registered and to generate a series of 3-dimensional plots. Traditional PITs and newer OTPs have been performed for their analysis. Specifically, the PEPs corresponding to the implementation of 4 PITs have been analyzed by collecting the measurements provided by a set of IMUs installed on a motion capture suit and their occupational risk assessments have been compared against those corresponding to newer OTPs. (3) Results: For the 4 PITs, the PEPs have been analyzed with the measured values from the IMUs, throughout the duration of each technique. The two traditional intervention techniques have scored higher than the new OTPs in the REBA system, the Assymetry angle, L5-Pelvis Shear and Joint Contac Forces, and the Total Muscle Power measurements. (4) Conclusions: It has been confirmed that the new OPTs minimize the risk of injuries, since their PEPs reached lower values than those corresponding to the traditional PITs, which are still being taught at Police academies.

Tomography based on cosmic muon absorption is a rising technique because of its versatility and its consolidation as geophysics tool over the past decade. It allows to address major societal issues such as long-term stability of natural and man-made large infrastructures or sustainable underwater management. Traditionally, muon trackers consist of hodoscopes or multilayer detectors. For applications with challenging available volumes or wide field of view required, a thin time projection chamber (TPC) associated with a Micromegas readout plane can provide a good tradeoff between compactness and performance. This paper details the design of such a TPC aiming at maximizing primary signal and minimizing track reconstruction artifacts. The results of the measurements performed during a case study addressing the aforementioned applications are discussed. The current works lines and perspectives of the project are also presented.

Pore Forming Toxins (PFTs), formed mainly by virulence factors of bacteria, belongs to Pore Forming Protein (PFP) family. Secreted as soluble monomers, they bind specific targets in membranes where their oligomerization and insertion place. Lysenin, a member of the PFTs, forms and oligomer after sphingomyelin binding, the so-called prepore, which become inserted forming a pore after a conformational change triggered by a pH decrease. In crowded conditions, oligomers tends to stay in prepore form because the prepore-to-pore transition is sterically blocked. In this study, we investigate the effect of calcium ions in those crowded conditions, finding that calcium act as a trigger for lysenin insertion. We localize the residues responsible for calcium sensitivity in a small α-helix. Our results are not only one of the few complete structural descriptions of prepore-to-pore transitions but the very first that involves a calcium triggering mechanism. The presence of glutamic or aspartic acids in the insertion domains could be an indication that calcium may be a general trigger for PFTs and more generally PFP.

This essay studies Afro-Asian sociocultural interactions in cultural production by or about Asian Latin Americans, with an emphasis on Cuba and Brazil. Among the recurrent characters are the black slave, the china mulata, or the black ally who expresses sympathy or even marries the Asian character. This reflects a common history of bondage shared by black slaves, Chinese coolies, and Japanese indentured workers, as well as a common history of marronage. These conflicts and alliances between Asians and blacks contest the official discourse of mestizaje (Spanish-indigenous dichotomies in Mexico and Andean countries, for example, or black and white binaries in Brazil and the Caribbean), which, under the guise of incorporating the Other, favored whiteness, all the while attempting to silence, ignore, or ultimately erase their worldviews and cultures.

Pimobendan is an inotropic and vasodilator drug with no sympathomimetic effects. This study aimed to evaluate the haemodynamic effects of pimobendan during anaesthesia in healthy senior dogs. A prospective, randomised, triple-blinded, placebo-controlled clinical study was conducted. Thirty-three dogs (median [range]: 9 [7, 12] years) were anaesthetised for surgical procedures. Dogs were randomly allocated into two groups: eighteen dogs received pimobendan 0.15 mg kg-1 IV (PIMOBENDAN) and 15, saline solutions 0.2 ml kg-1 IV (PLACEBO). Data were recorded before, 1 minute, 10 minutes and 20 minutes after injection. Velocity-time integral (VTI), peak-velocity (PV) and mean-acceleration (MA) were measured using an oesophageal Doppler monitor (ODM). Heart rate and mean arterial pressure were also registered. Data were analysed using a two-way ANOVA for trimmed means. Statistical differences were considered if p &lt; 0.05. Twenty minutes after injection, VTI (13.0 cm [10.4, 22.3]), PV (95.0 [83.0, 160] m sec-1), and MA (12.6 [9.40, 17.0] m sec-2) were higher in PIMOBENDAN when compared to PLACEBO (VTI: 10.5 [6.50, 17.4] cm, PV: 80.0 [62.0, 103] m sec-1 and MA: 10.2 [7.00, 16.0] m sec-2). No differences were observed in the rest of the variables. Using pimobendan during anaesthesia increases VTI, PV and MA measured by an ODM.

With the developments of smart technologies, the use of rare earth elements (REEs) knows a widespread use, thus, their importance as valuable and strategic metals boosted to levels never known before. Due to their scarcity in Earth crust, the recovery of these elements from secondary resources also knows further developments. Traditional pyrometallurgical and hydrometallurgical processing, though of wide use, in the recovery of these REEs, have some environmental drawbacks, thus, the development of new recovery approaches are under developments. Here, Solvometallurgy appeared as a friendly environmental technology, and ionic liquids and deep eutectic solvents re-sulted as a first-row chemicals to be used in the different unit operations used in solvometallurgical processing: leaching, liquid-liquid extraction, ion exchange (adsorption), precipitation and elec-trolysis. This manuscript reviewed the most recent literature concerning the use of ionic liquids and deep eutectic solvents in the recovery of REEs from various sources.

: Carcinoma-associated fibroblasts (CAFs) are highly accumulated in the tumor surrounding stroma of primary epithelial ovarian cancer (OC). CAFs exert important functions for the vascularization, growth and progression of ovarian tumor cells. However, no attention has been shown to their origin so far. It has been mainly assumed that CAFs in primary OC arise from the activation of resident fibroblasts. Here, we compare CAFs with ovarian location to CAFs found in peritoneal implants from patients with advanced OC. Our findings show that CAFs from primary tumors and peritoneal metastases share the expression of mesothelial-related markers. Therefore, as in peritoneal carcinomatosis, CAFs in primary ovarian carcinomas could be originated via a mesothelia-to-mesenchymal transition (MMT) process. The detection of mesothelial-derived CAFs in tumors confined to the ovary and associated biomarkers could be the key to early detection of peritoneal spread in affected patients.

Through the arrow decomposition of the Mueller matrix, respective sets of sixteen independent polarimetric images of biological tissues are obtained for enpolarizing, retarding and depolariz-ing descriptors. In addition to the mean intensity coefficient and the three indices of polarimetric purity, the absolute values and Poincaré orientations of diattenuation, polarizance, entrance re-tardance and exit retardance vectors are considered. In this work we use for the first time this set of polarimetric observables for the visualization of biological structures, both of animal and vege-tal origin. Results show images with enhanced visualization derived from the spatial variation of such significant polarimetric properties. The experimental results are discussed, showing the suit-ability of such set of observables for applications in biophotonics imaging, providing not only ex-cellent visualization of biological tissues, but also showing structures not visible in non-polarimetric images.

Endocrine therapy (ET) has established itself as an efficacious treatment for estrogen receptor-positive (ER+) breast cancers, with a reduction in recurrence rates and increased survival rates. The pre-surgical approach with chemotherapy (NCT) has become a common form of management for large, locally advanced or high-risk tumors. However, a good response to NCT is not usually expected in ER+ tumors. Good results with primary ET, mainly in elderly women, have encouraged studies in other stages of life, and nowadays neoadjuvant endocrine treatment (NET) has become a useful approach to many ER+ breast cancers. The aim of this review is to provide an update on the current state of art regarding the present and the future role of NET.

This work is a review of the current situation of type 1a diabetes mellitus in childhood. With a quick read, the reader will discover the current and immediate future challenges.

Natural deep eutectic solvents (NADES) have been shown as selective and environmentally friendly solvents for the extraction of bioactive compounds. However, studies on the solubility of low molecular weight carbohydrates (LMWC) in NADES are scarce. In this work, new solubility data of LMWC in NADES are provided and a new approach based on the use of these solvents for the efficient fractionation of bioactive carbohydrates was explored for the first time. Several mono- and disaccharides and three NADES based on choline chloride (ChCl) and different donors [2-ethylene glycol (EtG), glycerol (Gly) and ethanedioic acid dihydrate (Eth)] were considered. While degradation of carbohydrates, mainly ketoses, was detected with ChCl:Eth due to its acidic nature, ChCl:EtG and ChCl:Gly were found to be useful alternatives for selectively separating bioactive ketoses and their corresponding aldoses (e.g. lactulose/lactose and tagatose/galactose) present in equimolar binary mixtures. In addition, the usefulness of ChCl:EtG for the selective enrichment of lactulose to be used as food ingredient or nutraceutical was proven (from a 25% in the reaction mixture to a 56% in the purified sample). NADES could be used for the selective fractionation of value-added carbohydrates from interfering sugars for several applications including food science, engineering or pharmaceuticals.

As a model for economic and ecological systems, replicator dynamics represents a basic form of agent competition for finite resources. Here, we investigate the effects of stochastic resetting in this kind of processes. Random reset events abruptly lead individual resources to a small value from which dynamics must start anew. Numerical results show that resource distribution over the population of competing agents develops highly nonuniform profiles, exhibiting clustering and fluctuations with anomalous dependence on the population size. This non-standard statistical behavior jeopardizes an analytical treatment based on mean-field assumptions. We propose alternative simplified analytical approaches which provide a stylized description of entropy evolution for the clustered distribution of resources and explain the unusually slow decrease of fluctuations.

⦁ Introduction: The challenging context, resulting from a post-pandemic scenario, wars, and various natural disasters, does not allow for the ideal assurance of efficiency in the Agri-food supply chain. ⦁ Research significance Currently, Agri-food supply chains and Reverse logistics show critical characteristics such as centralization, limited flexibility, distrust, bureaucratization, Border and Documentary Compliance and there are problems about efficiency, security, and safety Agri-Food. using the Supply Chain Operations Reference (SCOR) framework, with the purpose of achieving Sustainable Development Goals, promoting transparency, traceability, and non-linearization of the agri-food supply chain. ⦁ Methodology The methodology is combined, the first part uses Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) identifying 72 articles with the principal contribution in the literature. The second part combines the application of Supply Chain Operations References (SCOR) and the Blockchain Technology aiming to decentralize the linear Agri-food Supply Chain and Reverse logistics. ⦁ Results/findings The results revealed a transformation of the traditional Agri-food Supply Chain, transitioning from linear management to a circular one. Additionally, after application it is possible to know a new way to manage the Reverse Logistic with more decentralization, flexibility, traceability, and reducing the unnecessary activities, which include Border and Documentary Compliance. The originality of this research is the novel combination of SCOR Model and Blockchain showing a priority about the key activities that add value and come close to the Sustainable practices. ⦁ Conclusion / Implications Based on the results is possible to conclude that the synergy between Blockchain and SCOR Model enables a new way to manage the Agri-food supply chain, improving efficiency and reducing activities without value. Also, it is possible to ensure that the practices of Reverse Logistics are improved based on terms of cost and time, and the reduction of the exposition on the Defective Product Risk. ⦁ Social Implications This paper could enhance confidence in all operations of the Agri-food supply chain as there are numerous issues regarding the security and safety of food. Additionally, it will aid in diminishing unnecessary activities and inefficient resource consumption practices, thereby accomplishing objectives 2 "zero hunger", 9 "Industry, Innovation, and Infrastructure", and 12 "Responsible consumption and production", along with their respective indicators. ⦁ Practical implications Regarding the practical implications, this research could contribute to analyses of the application of technology Blockchain in different sectors and identify the possible limitations when the main objective is to apply it on a big scale.

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

Smart cities will have a strong impact on the future of renewable energies as terms like sustainability and energy saving will be more common. In this sense, both of wind and hydrokinetic compact-size turbines, can play an important role in urban communities by providing energy to nearby consumption points in an environmentally suitable way. This work presents the experimental evaluation for a vertical-axis turbine Darrieus type, operating in an open-field wind tunnel and a confined water channel. Power and characteristic curves have been obtained for all test conditions, also the effect of turbine blockage has been evaluated under blockage values ranging from 6.8% to 35%. The peak power coefficient for the confined flow condition reached a value of 0.31 which is 1.5 times higher than the peak one for the experimental open field condition at the same Reynolds number and a blockage of 20%. Finally, two blockage correction equations have been applied to the water channel tests, which gave values quite similar to the results obtained from the wind tunnel.

Carbon footprint mitigation actions have become a key issue for companies involved in urban freight transport. The electrification of the delivery fleets is one of the crucial sustainable actions carried out. To this end, it is necessary to explore several fleet renewal strategies over a finite planning horizon evaluating different types of electric powertrains for light commercial vehicles. The primary goal of this purpose-built analysis is to assist and boost the fleet managers' decisions when transitioning to alternative-fuelled vans, intending to maximize cost savings and reduce greenhouse gas emissions inventory. The model presented in this work is a Multi-Objective Linear Programming hybrid analysis taking into account the vehicle and energy supply infrastructure costs and the emissions reported in each inventory scope following the Greenhouse Gas Protocol sustainability guidelines. From this perspective, the conducted research offers a novel approximation to fleet management problems enabling a break-down cost analysis and an evaluation of the annual emissions company report. The comprehensive numerical simulations carried out over different study scenarios in Spain demonstrate that the optimization approach does not only show effective fleet renewal strategies but also identifies critical factors that impact the fleet's competitiveness, offering valuable insights for fleet managers and policymakers to meet carbon footprint reductions in a cost-effectively way.

Medical brain image analysis is a necessary step in the Computers Assisted /Aided Diagnosis (CAD) systems. Advancements in both hardware and software in the past few years have led to improved segmentation and classification of various diseases. In the present work, we review the published literature on systems and algorithms that allow for classification, identification, and detection of White Matter Hyperintensities (WMHs) of brain MRI images specifically in cases of ischemic stroke and demyelinating diseases. For the selection criteria, we used the bibliometric networks. Out of a total of 140 documents we selected 38 articles that deal with the main objectives of this study. Based on the analysis and discussion of the revised documents, there is constant growth in the research and proposal of new models of deep learning to achieve the highest accuracy and reliability of the segmentation of ischemic and demyelinating lesions. Models with indicators (Dice Score, DSC: 0.99) were found, however with little practical application due to the uses of small datasets and lack of reproducibility. Therefore, the main conclusion is to establish multidisciplinary research groups to overcome the gap between CAD developments and their complete utilization in the clinical environment.

Soil erosion seriously affects vineyards. In this study, the influence of two plant covers on soil moisture and the effect of different physiographic conditions on runoff and sediment yields were evaluated in a rainfed vineyard formed by four fields (NE Spain) during 15 months. One field had spontaneous vegetation as plant cover and three fields had a cover crop of common sainfoin. The vineyards’ rows were dry and stable, whereas the inter-row areas were wet although very variable, and the corridors were wet and very stable. Soil moisture in the inter-row areas with Common sainfoin was much higher than in the rows (62% - 70%) whereas this difference was lower with spontaneous vegetation (40%). Two runoff and sediment traps (STs) were installed in two ephemeral gullies, and 26 time-integrated surveys (TIS) done. The mean and maximum runoff yields were 9.8 and 30.7 l TIS^–1 in ST2 and 13.5 and 30.2 l TIS^–1 in ST3. The mean turbidity was 333 and 19 g l^–1, and the maximum sediment yields were 41,260 and 2,778 g TIS^–1 in ST2 and ST3. Changes in the canopy covers (grapevines and plant covers) and rainfall parameters explained the runoff and sediment dynamics.

The formulation and analytic solution of a new mathematical model with constitutive curvature for analysis of tunnel ventilation shaft wall is proposed. Based on the Mindlin-Reissner theory for thick shells, this model also takes into account the shell constitutive curvature and considers an expression of the shear correction factor variable (αn) in terms of the thickness (h) and the radius of curvature (R). The main advantage of the proposed model is that it has the possibility to analyze thin, medium and thick tunnel ventilation shafts. As a result, two comparisons were made: the first one, between the new model and the Mindlin-Reissner model without constitutive curvature with the shear correction factor (α_n=6/5) as a constant, and the other, between the new model and the tridimensional numerical models (solids and shells) obtained by finite element method for different slenderness ratios (h/R). The limitation of the proposed model is that it is to be formulated for a general linear-elastic and axial-symmetrical state with continuous distribution of the mass.

This paper applies a new artificial intelligence architecture, the Temporal Fusion Transformer (TFT), for the joint GDP forecasting of 25 OECD countries at different time horizons. This new attention-based architecture offers significant advantages over other deep learning methods. First, results are interpretable since the impact of each explanatory variable on each forecast can be calculated. Second, it allows to visualize persistent temporal patterns and to identify significant events and different regimes. Third, it provides quantile regressions and permits to train the model on multiple time series from different distributions. Results suggest that TFTs outperform regression models, especially in periods of turbulence such as the COVID-19 shock. Interesting economic interpretations are obtained depending on whether the country is domestic demand-led or export-led growth. In essence, TFT is revealed as a new tool that artificial intelligence provides to economists and policy makers, with enormous prospects for the future.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

Agricultural expansion is altering the provision of ecosystem services and seriously affecting the well-being of the indigenous communities still living in forests. In this paper, we evaluate the impact of forest loss and degradation on the indigenous forest dependent communities of Eastern Salta, Argentina, between 2001 and 2015. First, we identified the demand area of ten final ecosystem services for 202 indigenous communities using participatory mapping data. Second, we calculated the remaining usage area using a deforestation geodatabase based on Landsat images. Third, we analyzed the significance of trends in forest productivity processing vegetation spectral indices from MODIS products. By last, we detected changes in the growing season length by evaluating monthly trends in spectral indices. Our results show a reduction of 21% in the area used by indigenous communities for capturing final ecosystem services, and significant negative trends in forest productivity for the demand area of 64% of the communities, indicating that the area of use is not only being reduced, but also remnant forest area is being degraded and the growing season is being shortened. These aspects indicate an important loss in the provision of ecosystem services that deeply affects the wellbeing of indigenous communities.

Soil salinity is a limiting factor in crop productivity. Inoculating crops with microorganisms adapted to salt stress is an alternative to increasing plant salinity tolerance. Few studies have simultaneously propagated arbuscular mycorrhizal fungi (AMF) and dark septate fungi (DSF) using different sources of native inoculum from halophyte plants, and evaluated their effectiveness. This study selected, in alfalfa plants as trap culture, the infectivity of 38 microbial consortia native from rhizospheric soil (19) or roots (19) coming from six halophyte plants, as well as their effectiveness in mitigating salinity stress. Inoculation with soil resulted in 26%-56% colonization by AMF and 12%-32% by DSF. Root inoculation produced 10%-56% and 8%-24% of colonization, respectively. There was no difference in the number of spores of AMF produced with both inoculum types. The effective consortia were selected based on low Na but high P and K shoot concentrations which is relevant for plant nutrition but more for salt stress mitigation. The microbial consortia selection is presented in a more novel and applicable context, which would allow for the production of native microbial inoculants adapted to salinity to diminish the harmful effects of salinity stress in glycophyte plants in the context of sustainable agriculture.

A significant part of the literature on innovative practice in medicine relates to seizing opportunities and curbing harms for patients in desperate situations. Unfortunately, the term innovation has multiple meanings and a rich rhetorical flourish that adds confusion and misunderstanding to an already difficult debate. This paper aims to enhance the current definition of innovative practice for medicine. First, we replace the term innovation with the more literal of new non-validated practice. To identify this meaning, we analyse the traditional research ethics’ distinction between research, validated practice, and innovation in the Belmont Report. Second, we propose the following explicit definition of new non-validated practice: the first or recent use of diagnostic, therapeutic or preventive interventions that introduce a significant change, with an insufficient level of evidence of safety or efficacy for regular healthcare, and with the main aim to benefit individual patients. This definition is a promising conceptual tool to inform empirical research, ethicists, and the harmonization of its regulation and legislation (e.g. right-to-try laws).

The growth in online child exploitation material is a significant challenge for European Law Enforcement Agencies (LEAs). One of the most important sources of such online information corresponds to audio material that needs to be analyzed to find evidence in a timely and practical manner. That is why LEAs require a next-generation AI-powered platform to process audio data from online sources. We propose the use of speech recognition and keyword spotting to transcribe audiovisual data and to detect the presence of keywords related to child abuse. The considered models are based on two of the most accurate neural-based architectures to date: Wav2vec2.0 and Whisper. The systems are tested under an extensive set of scenarios in different languages. Additionally, keeping in mind that obtaining data from LEAs is very sensitive, we explore the use of federated learning to have more robust systems for the addressed application, while maintaining the privacy of the data to LEAs. The considered models achieved a word error rate between 11% and 25%, depending on the language. In addition, the systems are able to recognize a set of spotted words with true positives rates between 82% and 98%, depending on the language. Finally, federated learning strategies show that they can maintain and even improve the performance of the systems when compared to centralized trained models. The proposed systems sit the basis for an AI-powered platform for automatic analysis of audio in the context of forensic applications within child abuse. The use of federated learning is also promising for the addressed scenario, where data privacy is an important issue to be managed.

This paper presents a new analytical method for obtaining new deformations compatibility equations or, new Saint-Venant’s identities, into the relative coordinate system with projected deformations by applying the hypothesis of the lineal shell theory in general flexion state. The method proposed generalizes the compatibility conditions established by A.L. Goldenveizer for the shell theory. On the other hand, the new equations include the deformations compatibility equations by other authors: Flügge, Saint-Venant, Love-Kirchhoff, Timoshenko, Goldenveizer, and Reissner-Mindlin. The results showed an increase of knowledge in general shell theory, and provide inverse and semi-inverse solutions, whose systems solution correspond to the hyper-statics degrees of the physical model, and not to their degrees of freedom.

Preterm birth (PB) is a leading cause of perinatal morbidity and mortality. PB prediction is per-formed by measuring cervical length, with a detection rate of around 70%. Although it is known that a cytokine-mediated inflammatory process is involved in the pathophysiology of PB, no screening method implemented in clinical practice includes cytokine levels as a predictor varia-ble. Here, we quantified cytokines in cervical-vaginal mucus of pregnant women (18-23.6 weeks of gestation) with high- or low-risk for PB determined by cervical length, collecting relevant obstetric information. IL-2, IL-6, IFN-γ, IL-4, and IL-10 were significantly higher in the high-risk group, while IL-1ra was lower. Two different models for PB prediction were created using the Random Forest machine-learning algorithm: the full model with 12 clinical variables and cyto-kine values, and the adjusted model, including the most significant variables -maternal age, IL-2, and cervical length- (detection rate 66 vs 87%, false positive rate 12 vs 3.33%, false negative rate 28 vs 6.66%, and area under the curve 0.722 vs 0.875, respectively). The adjusted model integrat-ing cytokines showed a detection rate 8 points higher than the gold standard calculator, which may allow us to identify PB risk more accurately and implement strategies for preventive in-terventions

Brain-computer interfaces (BCI) from electroencephalography (EEG) provide a practical approach to support human-technology interaction. In particular, motor imagery (MI) is a widely-used BCI paradigm that guides the mental trial of motor tasks without physical movement. Here, we present a deep learning methodology, named Kernel-based Regularized EEGNet (KREEGNet), leveled on Centered Kernel Alignment and Gaussian Functional Connectivity, explicitly designed for EEG-based MI classification. The approach proactively tackles the challenge of intra-subject variability brought on by noisy EEG records and the lack of spatial interpretability within end-to-end frameworks applied for MI classification. KREEGNet is a refinement of the widely accepted EEGNet architecture, featuring an additional kernel-based layer for regularized Gaussian functional connectivity estimation based on CKA. The superiority of KREEGNet is evidenced by our experimental results from binary and multi-class MI classification databases, outperforming the baseline EEGNet and other state-of-the-art methods. Further exploration of our model’s interpretability is conducted at individual and group levels, utilizing classification performance measures and pruned functional connectivities. Our approach is a suitable alternative for interpretable end-to-end EEG-BCI based on deep learning.

Several methods have been tried to estimate air temperature using satellite imagery. In this paper, the results of two machine learning algorithms, Support Vector Machine and Random Forest, are compared with Multivariate Linear Regression, TVX and Ordinary kriging. Several geographic, remote sensing and time variables are used as predictors. The validation is carried out using four different statistics on a daily basis allowing the use of ANOVA to compare the results. The main conclusion is that Random Forest with residual kriging produces the best results (R$^2$=0.612 $\pm$ 0.019, NSE=0.578 $\pm$ 0.025, RMSE=1.068 $\pm$ 0.027, PBIAS=-0.172 $\pm$ 0.046), whereas TVX produces the least accurate results. The environmental conditions in the study area are not really suited to TVX, moreover this method only takes into account satellite data. On the other hand, regression methods (Support Vector Machine, Random Forest and Multivariate Linear Regression) use several parameters that are easily calculated from a Digital Elevation Model, adding very little difficulty to the use of satellite data alone. The most important variables in the Random Forest Model were satellite temperature, potential irradiation and cdayt, a cosine transformation of the julian day.

Food allergies have increased significantly in recent decades, with shellfish being a leading cause of food allergy and anaphylaxis worldwide, affecting both children and adults. The prevalence of shellfish allergies is estimated to be approximately 0.5-2.5% of the general population, varying significantly by geographical location, age, and consumption habits. Although mollusk consumption has risen, the prevalence of mollusk allergies remains unknown. While extensive research has focused on crustacean allergies, mollusk allergies, particularly those related to gastropods, have received comparatively less attention. Clinical manifestations of shellfish allergy range from localized symptoms to life-threatening systemic reactions, such as anaphylaxis. Notably, severe bronchospasm is a predominant clinical feature in cases involving gastropods. Several allergens have been identified in mollusks, including paramyosin, tropomyosin, and sarcoplasmic calcium-binding protein. In gastropods, documented allergens include tropomyosin, paramyosin, the heavy chain of myosin, and Der p 4 amylase. Diagnosis typically involves a thorough clinical history, skin testing, in vitro quantification of immunoglobulin (Ig) E, and confirmation through oral challenge, although the latter is reserved for selected cases. This review highlights the limited research on gastropod allergy, the identified allergens to date, and the necessity for further investigations to better understand the implications of shellfish allergy within this class.

Deep Learning (DL) has made significant advances in computer vision with the advent of Vision Transformers (ViT). Unlike Convolutional Neural Networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then use residual connections to feed these features directly into a fully networked multilayer perceptron head. In hospitals, hematologists prepare peripheral blood smears (PBSs) and read them under a medical microscope to detect abnormalities in blood counts such as leukemia. However, this task is time-consuming and prone to human error. This study investigates the transfer learning process of Google ViT and ImageNet CNNs to automate the reading of PBSs. The study used two online PBS datasets, PBC and BCCD, and transferred them into balanced datasets to investigate the influence of data amount and noise immunity on both neural networks. The PBC results show that Google ViT is an excellent DL neural solution for data scarcity. The BCCD results show that Google ViT is superior to ImageNet CNNs in dealing with unclean, noisy image data because it is able to extract both global and local features and use residual connections, despite the additional time and computational overhead.

The administration of regional neuraxial analgesia for pain relief during labor is widely recognized as a safe and effective method involving medication delivery into the epidural or subarachnoid space in the lower back. This study proposes an innovative semantic image segmentation methodology emphasizing enhanced interpretability using convolutional Random Fourier Features and layer-wise weighted class-activation maps tailored explicitly for foot segmentation in regional analgesia monitoring. Namely, our contribution is twofold: i) a novel Random Fourier Features layer is introduced to deal with image data to enhance three well-known architectures (FCN, UNet, and ResUNet); ii) three novel quantitive measures are presented to evaluate the interpretability of a given deep learning model devoted to segmentation tasks. Our approach is rigorously evaluated on a demanding dataset of foot thermal images from pregnant women who received epidural anesthesia. Its small size and considerable variability characterize the dataset. Our validation results demonstrate that the proposed methodology not only achieves competitive foot segmentation performance but also significantly enhances the explainability of the process, rendering it well-suited for applications such as epidural insertion during labor.

Anaerobic digestion is a biological process that transforms high-strength organic effluents into biogas with multiple benefits. However, concurrent with organics' biological transformation, a liquid phase with a high solid content is also derived from this process. Valorizing this fraction is not an easy task if an agronomic application cannot be considered as a suitable option. The thermal valorization of this fraction allows for energy extraction, but also gives rise to additional capital investment and increases the energy demand of the global process. In addition, the thermal treatment of digestate has to deal with a mineralized material. The changes in organic matter due to anaerobic stabilization were studied in the present manuscript, by evaluating the thermal behavior of samples, activation energy and organic transformation using FTIR spectroscopy. Digested samples of a mixture composed of manure and glycerin (5% v/v) were studied. The stabilization caused a dramatic decrease in aliphatic compounds, greatly increasing the mineral content of the sample. Thermal valorization of digestates must consider the lower energy content and more complex structure of these materials, with higher content of lignin and protein-type compounds.

The transformation of the state of polarization of a light beam by its linear interaction with a material medium can be modeled through the Stokes-Mueller formalism. The Mueller matrix associated with a given interaction depends on many aspects of the measurement configuration. In particular, different Mueller matrices can be measured for a fixed material sample depending on the spectral profile of the light probe. For a given light probe and a given sample with inhomogeneous spatial behavior, the polarimetric descriptors of the point-to-point Mueller matrices can be mapped leading to respective polarimetric images. The procedure can be repeated sequentially by using light probes with different central frequencies. In addition, the point-to-point Mueller matrices consecutively measured can be combined synthetically through convex sums leading to respective new Mueller matrices, in general with increased polarimetric randomness, thus exhibiting specific values for the associated polarimetric descriptors, including the indices of polarimetric purity, and generating new polarimetric images which are different from those obtained from the original Mueller matrices. In this work, the fundamentals for such synthetic generation of additional polarimetric images are described, providing a new tool that enhances the exploitation of Mueller polarimetry.

Parallel decompositions have proved to be powerful tools for the analysis and interpretation of the physical information provided by Mueller matrices experimentally obtained. In this work, the procedure for the so-called arbitrary decomposition of Mueller matrices is validated through its application to a set of representative experimentally determined Mueller matrices. The covariance and passivity criteria required for the physical realizability of the Mueller matrices involved in the parallel decompositions are integrated in the procedure, which ensures the physical consistency of the results presented.

Background: Pteropodine (PT) is a component of some plants with potentially useful pharmaco-logical activities for humans. This compound has biomedical properties related to the modulation of the immune system, nervous system, and inflammatory processes. This study addresses the an-ti-inflammatory and antioxidant capacity of pteropodin in a murine model of arthritis and induced edema of the mouse ear. Methods: To evaluate the anti-inflammatory activity, we used the reversed passive Arthus reaction (RPAR), which includes the rat paw edema test, the rat pleurisy test, and a mouse ear edema model. The antioxidant effect was evaluated by determining the myeloperoxidase enzyme activity. Results: PT showed an anti-inflammatory effect in the different specific and non-specific tests. We found a 52 to 74% of inhibitory effect of PT in the rat paw edema test, 52% of reduction of the pleural exudate volume, and low neutrophil count (28%), when compared to the control group. We also found a 81% of inflammatory inhibition of the ear edema, and a significant myeloperoxidase enzyme inhibition by the three doses of PT. Conclusions: PT exerted a potent an-ti-inflammatory effect in the acute inflammation model in rodents.

This study aims to better understand students who attend the Basic Vocational Training Cycles (FPB) regarding the measures to ensure diversity. This quantitative research project approximates the perception of students concerning their passage through their previous studies and their satisfaction and goals after finishing the school year. The sample con-sists of 352 students from Cordoba (Spain). A questionnaire has been used which follows the CIPP model. After the exploratory factor analysis was completed with the different groups of items and their descriptive analysis, various tests were carried out to consider the hypotheses (Pearson's correlation (r), one-factor analysis of variance and repeated ANOVA measures). The results indicate that the educational interest of the students is ac-ademic and professional. Likewise, there is no relationship detected between the appear-ance of socio-professional goals and average academic levels and the attributions with re-spect to repetitions of previous courses, although these goals vary depending on the satis-faction shown by the students with respect to the cycles. We conclude that the course of the FPB influences the adoption of decisions regarding academic-professional projects.

The importance of rare earth elements as the basis in the development of new technologies or the improvement of the used ones, made of a necessity its recovery, besides that from raw materials, from waste materials. In this recovery, Hydrometallurgy and its derivative Solvometallurgy, play a key role due to its operational characteristics, which are emphasized with the use of ionic liquids. The manuscript reviewed the most recent advances (2023 and 2024 years) about the use of ionic liquids in the unit operations (leaching and separation technologies) aimed to the recovery of these valuable and strategic metals. Moreover, a comprehensive review about the use of these chemicals in the development of advanced materials containing some of these rare earth elements is presented.

Neurodegeneration with brain iron accumulation (NBIA) is a group of rare neurogenetic dis-orders frequently associated with iron accumulation in the basal nuclei of the brain. Among NBIA subtypes, β -propeller protein-associated neurodegeneration (BPAN) is associated with mutations in the autophagy gene WDR45. The aim of this study was to demonstrate autophagic defects and secondary pathological con-sequences in cellular models derived from two patient harboring WDR45 mutations. Both protein and mRNA expression levels of WDR45 were decreased in patient-derived fibro-blasts. In addition, the increase of LC3B upon treatments with autophagy inducers or inhibitors was lower in mutant cells compared to control cells, suggesting decreased autophagosome formation and impaired autophagic flux. Transmission electron microscopy (TEM) analysis showed mitochondrial vacuolization associated with accumulation of lipofuscin-like aggregates containing undegraded material. Autophagy dysregulation was also associated with iron ac-cumulation and lipid peroxidation. In addition, mutant fibroblasts showed altered mitochon-drial bioenergetics. Antioxidants such as pantothenate, vitamin E and α-lipoic prevented lipid peroxidation and iron accumulation. However, antioxidants were not able to correct the ex-pression levels of WDR45 neither the autophagy defect nor cell bioenergetics. Our study demonstrated that WDR45 mutations in BPAN cellular models impaired autophagy, iron metabolism and cell bioenergetics. Antioxidant partially improved cell physiopathology, however autophagy and cell bioenergetics remained affected.

The linkage between the salt wedge, tidal patterns, and the Magdalena River discharge is established by assessing the ensuing parameters: stratification (ϵ), buoyancy frequency (β), potential energy anomaly (φ), Richardson number (RL), and bottom turbulent energy production (P). The salinity, temperature, density, and water velocity data utilized were derived from MOHID 3D, a previously tailored and validated model for the Magdalena River Estuary. To grasp the dynamics of the river, a flow regime analysis was conducted during both wet and dry climatic seasons of the Colombian Caribbean. The utilization of this model aimed to delineate the estuary's spatial reach, considering flow rates spanning from 2000 to 6500 m³/s across two tidal cycles. This approach facilitates the prediction of the position, stability, and stratification degree of the salt front. Among the conclusions drawn, it is highlighted that: 1. The river flow serves as the principal conditioning agent for the system, inducing a strong estuary response to weather stations; 2. The extent of wedge intrusion and the river discharge exhibit a non-linear, inversely correlation; 3. Tidal waves cause differences of up to 1000 m in the horizontal extent of the wedge; 4. Widespread channel erosion occurs during the rainy season when the salt intrusion does not exceed 2 km; 5. Flocculation processes intensify during the transition between dry and wet seasons; 6. The stability of the salt layering and the consolidation of the FSI-TMZ are contingent upon the geometric attributes of the channel.

The potential of biological consortia designed for laccase production and dye treatment is discussed in this review. The poor yields in laccase production and low efficiency in dye decolorization of monoculture-based treatments has encouraged the use of designed biological consortia. A consortium is a system where the growth of two or more organisms, chosen to improve a particular bioprocess, is induced in the same medium. Chemical and natural mediators are being replaced by consortia for the production of laccases because, in addition to being less toxic, they induce new enzyme isoforms and lead to high laccase yields. On the other hand, consortia act synergistically in the decolorization of azo dyes through the enzymes they produce, so overall degradation is improved. Designed consortia are an attractive alternative still in development that could provide new biotechnological tools for the treatment of textile effluents.

Type 2 Diabetes Mellitus and Alzheimer's disease are two diseases with a high incidence today that share similar pathophysiological mechanisms suggesting a potential causal relationship between them. In fact, Alzheimer-associated Mellitus Diabetes is also known as Type 3 Diabetes Mellitus and constitutes a diabetes intricately linked to Alzheimer's disease. Central to this association is insulin resistance, a key factor leading to decreased insulin sensitivity, hyperglycemia, and impaired glucose uptake. Because of this, the brain is altered resulting in energy deficits and neuronal damage associated with neurodegenerative disorder characteristic of Alzheimer's disease. Both diseases exhibit common biochemical and physiological characteristics such as inflammation, mitochondrial dysfunction, oxidative stress, and the formation of advanced glycation end products. Understanding the complex pathophysiology of Type 3 Mellitus Diabetes and identifying common features shared with Diabetes and Alzheimer's disease are essential steps towards potential therapeutic interventions targeting the insulin resistance pathway. The authors of this review on the relationships between type 2 diabetes and Alzheimer's disease have developed two works. In the first (Relationships between Type 2 Diabetes Mellitus and Alzheimer's Disease. I. Common pathogenic mechanisms), authors explore the shared (physiological, genetics and molecular) pathological changes occurring in Type 2 Mellitus Diabetes and Alzheimer's disease as well as pathways such as AMPK, PPARγ, cAMP, and PI3K/Akt as potential targets for managing Type 3 Diabetes Mellitus. By exploring these intricate mechanisms, the goal is to uncover their interdependencies and facilitate the discovery of innovative pharmacological and nutritional (epigenetics) strategies. In the second paper (Relationships between Type 2 Diabetes Mellitus and Alzheimer's Disease. II Potential therapies) we describe possible nutritional intervention, particularly dietary patterns and phytochemicals that can enhance the effects of pharmaceutical drugs designed against pathological mechanisms involved in the complex dual disease Type 2 Diabetes Mellitus and Alzheimer's disease (or in Type 3 Diabetes Mellitus as other authors consider).

Mayaro virus (MAYV) hijacks the host´s cell machinery to effectively replicate. The mitogen-activated protein kinases (MAPKs) p38, JNK and ERK1/2 have emerged as crucial cellular factors implicated in different stages of the viral cycle. However, whether MAYV uses these MAPKs to competently replicate has not yet been determined. The aim of this study was to evaluate the impact of MAPKs inhibition on MAYV replication using primary human dermal fibroblasts (HDFs) and HeLa cells. Viral yields in supernatants from MAYV-infected cells treated or untreated with inhibitors SB203580, SP600125, U0126 or Losmapimod were quantified using plaque assay. Also, viral protein expression was analyzed using immunoblot and immunofluorescence. Knockdown of p38⍺/p38β isoforms was performed in HDFs using the PROTACs molecule NR-7h. Our data demonstrated that HDFs are highly susceptible to MAYV infection. SB203580, a p38 inhibitor, reduced MAYV replication in a dose-dependent manner in both HDFs and HeLa cells. Additionally, SB203580 significantly decreased viral E1 protein expression. Similarly, knockdown or inhibition of p38⍺/p38β isoforms with NR-7h or Losmapimod, respectively, affected MAYV replication in a dose-dependent manner. Collectively, these findings suggest that p38 could play an important role in MAYV replication and could serve as a therapeutic target to control MAYV infection.

The paper proposes, through an experimental method, a conceptualisation of theoretical-methodological and practical guidelines for the project on the system of collective open spaces, residual areas, abandoned areas that characterise the contemporary city, both in the urban contexts of the historical city, and in the more marginal areas of the modern suburbs. This methodology was experimented on an historical neighbourhood in Rome (San Lorenzo discrict) starting from the results of some researches conducted in collaboration between Sapienza University of Rome and the Escuela de Architettura, Universidad San Jorge and some design experiments conducted by Gràvalosdimonte design studio. This methodology and experimentation combines the theme of the inter-scalarity of the project (territorial, urban and local scale) with the themes of the flexibility and proximity of functions with respect to local instances and contingencies caused by the pandemic situation and by the sustainability perspectives, with particular reference to the need for urban health, the dialectic between public and private space in the perspective of the notion of common good, the bottom-up project for the construction of proximity spaces and plurality in the decision-making process.

This study investigates the effect of scaffold architecture on bone regeneration, focusing on 3D-printed polylactic acid-bioceramic calcium phosphate (PLA-bioCaP) composite scaffolds in rabbit femoral condyle critical defects. To assess their influence on bone healing and scaffold performance, we explored two distinct scaffold designs, alternate and helical laydown patterns. The scaffolds were meticulously characterized for pore size, strut thickness, porosity, pore accessibility, and mechanical properties. The in vivo efficacy of these scaffolds was evaluated using a rabbit femoral condyle critical defect model. Our findings indicate that both scaffold architectures are biocompatible and support bone formation. The helical scaffolds, characterized by larger pore sizes and higher porosity, demonstrated significantly greater bone regeneration than the alternate structures. However, their lower mechanical strength presented limitations for use in load-bearing sites. This study highlights the importance of scaffold architecture in bone tissue engineering and underscores the need to balance porosity and mechanical strength for optimal bone regeneration. The findings provide crucial insights for the design of 3D- printed scaffolds in clinical applications, particularly in the context of critical-sized bone defects. The study also outlines potential areas for future research, including exploring hybrid scaffold designs to achieve optimal porosity without compromising mechanical integrity.

People with Down syndrome present cognitive difficulties that affect their reading skills. In this study we present results about the use of gestural interaction with Kinect sensor to improve the reading skills of students with Down syndrome. Following a case of study method for small samples with disabilities, measuring different variables related to reading skills in an experimental group and in a control group. We found improvements in the visual association, visual comprehension, sequential memory, and visual integration after this stimulation in the experimental group compared to the control group. Also, we found that the number of error and delay time of interaction decrease between sessions in the experimental group.

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

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020 and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the three analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico's most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last few years. These situations have strongly influenced the spatial-temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

The accumulation of microorganisms, plants, algae, or small animals on wet surfaces that have a mechanical function causes biofouling, which can result in structural or other functional deficiencies. The maritime shipping industry must constantly manage biofouling to optimize operational performance, which is a common and long-lasting problem. It can occur in any metal structure in contact or submerged in ocean water, which represents additional costs in terms of repairs and maintenance. This study is focused on the production of antifouling coatings, made with nanoparticles of copper selenide (CuSe) modified with gum arabic, within a water-base acrylic polymeric matrix. During the curing of the acrylic resin, the CuSe NPs remain embedded in the resin but this does not prevent the release of ions. The coatings presented to release copper and selenium ions for up to 80 days, selenium was the element that was released the most. The adhesion of film coatings to metallic substrates showed good adhesion, scale 5B (ASTM D3359 standard). Antimicrobial activity tests show that the coatings have an inhibitory effect on Escherichia coli and Candida albicans. The effect being more noticeable when the coating is detached from the substrate and placed on a growing medium, than compared to the coating on a substrate. Scanning electron microscopy (SEM) observations show that nanostructured CuSe coatings are made up of rod-shaped and spherical particles whose range ranges from 12 to 25 nm. The Energy Dispersive X-ray spectroscopy (EDS) studies showed that the ratio of selenium nanoparticles is greater than that of copper and that their distribution is homogeneous

Though nowadays germanium do not reach the range of popularity than other metals, i.e. rare earth elements, its utility in target industries makes of it also a strategic metal. Though germanium can be find in a series of raw materials, the principal source for its recovery is from secondary wastes of the zinc industry, and also, the recycle of germanium-bearing waste materials is becoming of interest. In this recovery, Hydrometallurgy is performing a key role to the successful achievement of this goal. The present work reviews the most recent applications (2023 and 2024 years) of hydrometallurgical operations on the recovery of germanium from different solid and liquid sources.

The contribution of academics and researchers to the discussion around sustainable rural development planning and its impact on rural communities has grown exponentially in recent years. Understanding trends in sustainable rural development research requires considering the different factors involved and affecting people from a holistic approach. This review examines, through bibliometric studies, the scientific knowledge generated on sustainable rural development planning in the last 50 years, analyzing 6,895 articles published in journals between 1970 and 2020. The results reveal the existence of three clusters and an important growth is observed to respond to the continuous needs in relation to sustainable rural development. This research shows the evolution of a new approach for the planning of sustainable rural development projects in postmodernity: Working with People (WWP). This WWP model, as a conceptual framework from social learning has been validated as a novel proposal in numerous contexts. The bibliometric analysis shows an evolution "From Putting the Last first" to "Working with People in Rural Development" research and the contributions of influential teachers such as Chambers and Cernea. These bibliometric analyses demonstrate the correct approach of WWP model, and open new fields of research in the planning of sustainable rural development projects.

Inside Central Nervous System (CNS) appears neurons and glia cells. There are more glial cells than neurons and have more functions than neurons. Glia name represents different kind of cells, ones from neural origin (astrocytes, radial glia, and oligodendroglia), and others from blood monocytes (microglia). During ontogeny, neurons appear first (rat fetal 15th) and after astrocytes (rat fetal 21th) indicating a bigger importance function in the CNS. Also, during the phylogeny, reptiles have less astrocytes compared to neurons and in humans, astrocytes are double in number than neurons. This data, perhaps means that astrocytes are more special cells and work in memory and learning? Astrocytes have an important role in different mechanisms protecting CNS across the production of antioxidant and anti-inflammatory proteins, cleaning extracellular medium and helping neurons to communicate with each other correctly. Inflammatory mediators production are important to prevent changes in normal physiology. But, excessive or continue production leads to many diseases, such as Alzheimer's disease (AD), Sclerosis Lateral Amyotrophic (ELA), Multiple sclerosis (MS), and neurodevelopment diseases, like Bipolar disorder, Schizophrenia, and Autism's symptomatology. Different drugs and thecniques can reverse oxidative stress and/or inflammatory excess. This review is intended to serve as an approximation to the field.

The implementation of sustainable practices, such as the use of renewable sources and efficient technologies, is crucial for reducing climate change. Energy efficiency is highly important on a global scale due to its relationship with climate change, aiming to minimize environmental impact. In Spain, renewable energy policies have increased self-sufficiency and reduced the use of fossil fuels. Optimizing energy consumption in residences, buildings, and industries is essential for improving efficiency. This was taken into consideration for conducting this study, focusing on the residential sector. The desire to understand the level of energy efficiency in Extremadura drove this project, which focuses on collecting and analyzing data on a set of homes located in the au-tonomous community of Extremadura, with the purpose of evaluating their energy efficiency. To achieve this, a computer tool will be employed to provide a detailed view of the different levels of energy efficiency present in the community. In addition to data collection and analysis, research will be conducted to identify areas for improvement. This will allow proposing a series of specific measures that users can implement to optimize energy efficiency in their homes, adapting them to the particular characteristics of each residence.

This work focuses on analyzing acoustic emission (AE) signals as a means to predict failure in structures. Two main approaches are considered: (i) long-range correlation analysis using both the Hurst (H) and the Detrended Fluctuation Analysis (DFA) exponents, and (ii) natural time domain (NT) analysis. These methodologies are applied to the data collected from two application examples: a glass fiber reinforced polymeric plate and a spaghetti bridge model, where both structures were subjected to increasing loads until collapse. A traditional (AE) signal analysis is also performed to reference the study of the other methods. Results indicate that the proposed methods yield a reliable indication of failure in the studied structures.

Background. Transcatheter edge-to-edge repair (TEER) is a safe and effective treatment in symptomatic patients with mitral regurgitation (MR). We aimed to investigate the short-term impact of mitral TEER on left ventricular (LV) performance and identify echocardiographic prognostic indicators. Methods. Seventy-eight patients with severe MR (organic and functional etiologies) were included retrospectively. All patients had a baseline and short-term echocardi-ography after TEER and were followed up for the primary composite endpoint (heart failure hos-pitalization and cardiovascular death) over a median period of 13 months. Results. A significant decrease in left ventricular ejection fraction (LVEF), all myocardial work indices (except global wasted work), and left atrial reservoir were observed after TEER. Additionally, there was an im-provement in the pulmonary artery systolic pressure and tricuspid annular plane systolic excur-sion/pulmonary artery systolic pressure (TAPSE/PASP) ratio. 34% of all patients presented the primary composite endpoint. A TAPSE/PASP ratio post-TEER < 0.47 (HR: 4.76, p-value = 0.039), and left atrial reservoir post-TEER < 9.0% (HR: 2.77, p-value = 0.047) were independently associ-ated with the primary endpoint. Conclusions. Echocardiography post-TEER reflects impairment in ventricular performance due to preload reduction and right ventricular to pulmonary artery coupling improvement. Short-term echocardiography after TEER identifies high-risk patients who could benefit from a close clinical follow-up.

Recent advances in artificial intelligence combined with behavioral sciences have led to the development of cutting-edge tools for recognizing human emotions based on text, video, audio, and physiological data. However, these data sources are expensive, intrusive, and regulated, unlike plants which have been shown to be sensitive to human steps and sounds. A methodology is proposed to use plants as human emotion detectors. Electrical signals from plants are tracked and labeled based on video data. Labeled data are then used for classification. MLP, biLSTM, MFCC-CNN, MFCC-ResNet, and additionally, Random Forests, 1-Dimensional CNN, and biLSTM without windowing models are set using a grid search algorithm with cross-validation. Finally, best-parameterized models are trained and used with the test set for classification. The performance of this methodology is measured with a case study with 54 participants, who were watching an emotionally charged video, as ground truth their facial emotions were simultaneously measured using face emotion analysis. The Random Forest model shows the best performance, particularly in recognizing high-arousal emotions, achieving an overall weighted accuracy of 55.2% and demonstrating high weighted recall in emotions such as fear 61.0% and happiness 60.4%. The MFCC-ResNet model offers decently balanced results, with Accuracy(MFCC-ResNet)=0.318 and Recall (MFCC-ResNet)=0.324. With the MFCC-ResNet model fear and anger are recognized with 75% and 50% recall respectively. Thus, using plants as an emotion recognition tool seems worth investigating, addressing both cost and privacy concerns.

The study also found that older age was a protective factor in prospective studies. The consistency of results across different study designs and sensitivity analyses further supported the robustness of the findings. It is important to note that the existing literature on revictimization in women facing intimate partner violence is limited and exhibits significant heterogeneity in terms of methodology and conceptual frameworks.

Firms are increasingly organized around the client. At the same time, there is customer pressure on green and sustainable organizations. The purpose of this paper is to map the current state of the research in the domain of customer-centric organizations from a sustainable perspective. We conducted a bibliometric analysis from published documents between 1990 and 2020. Key findings indicate that research on customer centricity and sustainability has increased in recent years and that the topic is structured into 3 clusters: (1) Sustainability; (2) Customer-Centric Perspective, and Sustainable Development; and (3) Customer Experience and Sales. Moreover, new concepts and technologies have been introduced during the last three years. The implementation of a bibliometric methodology and the focus given to the definition, the relationships, and the evolution of the three main clusters within the topic are the characteristics that differentiate our study from other publications or reviews in the field of research. This paper is beneficial for practitioners who aim to deploy the customer centricity approach in their firms from a sustainable perspective.

The experimental determination of the relative biological effectiveness of thermal neutron factors is fundamental in Boron Neutron Capture Therapy. Present values have been obtained using mixed beams consisting of both neutrons and photons of various energies. A common weighting factor has been used for both thermal and fast neutron doses, although such an approach has been questioned. At the nuclear reactor of the Institut Laue-Langevin a pure low-energy neutron beam has been used to determine thermal neutron relative biological effectiveness factors. Different tumor cell lines, corresponding to glioblastoma, melanoma, and head and neck squamous cell carcinoma, and non-tumor cell lines (lung fibroblast and embryonic kidney) have been irradiated using an experimental arrangement designed to minimise neutron-induced secondary gamma radiation. Additionally, the cells were irradiated with photons at a medical linear accelerator, providing reference data for comparison with that from neutron irradiation. Survival and proliferation were studied after irradiation, yielding the Relative Biological Effectiveness corresponding to the damage of thermal neutrons for the different tissue types.

Non-typhoid salmonellosis is a common and problematic foodborne zoonotic disease in which pork and pork products can be an important potential source of infection. In order to prevent this disease important efforts to monitor the situation in the main source, livestock, are conducted in most developed countries. In the European Union EFSA and ECDC compile information at the member state level, even though important differences in production systems and surveillance systems exist. Here, Salmonella surveillance systems in one of the main sources of foodborne salmonellosis, swine, and humans in Spain were reviewed to identify potential gaps and discuss potential ways of integration under a One Health approach. Despite the extensive information generated through the surveillance activities source attribution can be only routinely performed through ad-hoc outbreak investigations, and national reports on human outbreaks do not provide sufficiently detailed information to gain a better understanding of the epidemiology of the pathogen. Human and animal monitoring of Salmonella would benefit from a better exchange of information and collaboration. Analysis of spatio-temporal trends in livestock and humans could help to identify likely sources of infection and to target surveillance efforts in areas with higher prevalence or where specific strains are found.

Health care workers (HCWs), specifically dentists, are at the front line for acquiring blood-borne virus infections. The highest proportion of occupational transmission is through percutaneous injuries via hollow-bore needles. Several studies around the world have reported that hepatitis viruses and human immunodeficiency virus are the main pathogens for most cases of occupationally acquired blood-borne infection. We aim to investigate the prevalence of hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis E virus (HEV), and human immunodeficiency virus (HIV) among Mexican dentists. Methods. We included 159 dentists who attended the annual meeting at the Medica Sur Clinic & Foundation held in Mexico City in May 2016. A survey was applied in order to obtain data of occupational exposure to blood-borne viruses (BBV). Serum samples were screened serologically using enzyme-linked immunosorbent assays. Results. Two dentists (1.2%) were positive for antibodies against HCV antigen, one (0.6%) was positive for antibodies against HBV antigen and three (1.8%) were positive for the detection of IgG antibodies against HEV. Two cases (1.2%) were positive for antibodies against HIV. Conclusions. The infection by HEV was the most prevalent among dentists. However, the prevalence of BBV in dentists was similar to that in the general population.

Background: The validation of measuring instruments in health is a requirement to be able to use them safely and reliably. The Short Physical Performance Battery (SPPB) tool is an instrument widely used in the clinic and validated in numerous countries and languages and for different populations. The objective of this research was to determine the psychometric properties of SPPB for a sample composed of institutionalized Spanish older adults. Methods: Multicenter study of the psychometric properties of the Short Physical Performance Battery tool with a convenience sample of 194 institutionalized older adults. Reliability (internal consistency), validity (construct validity and convergent validity) tests were performed. Results: The results show a very good internal consistency, construct validity and convergent validity. In addition, the factorial structure of the SPPB is provided, which reflects that it is a unidimensional scale. Conclusions: In conclusion, the Short Physical Performance Battery is a valid and reliable tool for use with institutionalized older adults. Its use is recommended as part of the Comprehensive Geriatric Assessment for the evaluation of the physical or functional sphere. Authors should include one of the following statements about the registration status of the manuscript here: This study was prospectively registered and approved by the Ethics Committee of the University of Burgos (IR 11/2018).

The effect of sonication on the molecular characteristics of poliacrylic acid (Carbopol® Ultrez 10) and its rheological behavior in aqueous dispersions and microgels containing 0.25 wt. % of the polymer was analyzed in this work by rheometry, weight-average molecular weight (Mw) measurements via static light scattering (SLS), Fourier transform infrared (FTIR) spectroscopy and confocal microscopy. For this, the precursor dispersion and the microgels were sonicated in a commercial ultrasound bath at constant power and different times. We observed a softening of the microgel microstructure consisting of a systematic decrease in its shear modulus, yield stress and viscosity with increasing sonication time, while their overall Herschel-Bulkley (H-B) behavior was preserved. SLS measurements evidenced a reduction of Mw of polyacrylic acid with sonication time. Separately, FTIR measurements indicate that sonication produces scission in the C-C links of the Carbopol® backbone, which results in chains with the same chemistry but lower molecular weight. Finally, confocal microscopy measurements revealed a concomitant diminution of the size of the microsponge domains with sonication time, which is reflected in a softer microstructure resulting from reduction of the molecular weight of polyacrylic acid. The present results indicate that both the microstructure and the rheological behavior of Carbopol® microgels, in particular, and complex fluids in general, may be manipulated or tailored by high-power ultrasonication.

There is consensus over the fact that urban green areas contribute to the quality of life of their inhabitants. So, efficient city management must assess whether the population has access to green areas and their quality in relation to vegetation, facilities or furnishings, for example. Therefore, the objective set is to establish the environmental justice of urban parks in Tarragona (Spain) by developing a Park Quality Index (PQI) and the sociodemographic characteristics (level of studies, Human Development Index [HDI], home sale and rental prices) of the population living within 300 metres of a park. To prepare this, a GIS-integrated Multi-Criteria Evaluation (MCE) has been produced. The results show that the green areas have low accessibility and availability and that most parks obtain an average-low PQI, with the best- valued aspect being the vegetation and the worst the facilities. As for the degree of environmental justice, a casual relationship emerges between the PQI and the indicators used. The average value of the home sale prices is the one that shows the greatest correlation. These results can be used together with participatory procedures as a basis for identifying places with greater inequality, and for selecting the more effective actions that enable increasing environmental justice with respect to green areas.

(1) Background: Mindfulness-based interventions (MBIs) have shown interesting preliminary ef-fects over self-regulation processes in early adolescence. However, interventions usually integrate various types of practices with no clarity about the specific effect of each of them over attentional, emotional, and behavioral regulation. The objective of this research was to evaluate the effect of two MBIs, one focused on classic attentional practices and another one focused on the recognition and expression of emotions, over attentional, emotional, and behavioral self-regulation in early adolescents. (2) Method: An experimental method was carried out. A sample of 70 children be-tween 8 and 12 years old were randomized and assigned to three experimental conditions: 1) MBI with a focus on attentional practices, 2) MBI with a focus on recognition and expression of emotions, 3) control group, waiting list. The programs lasted 8 weeks, with a weekly 1-hour online synchronic session, plus home practices. Children were evaluated before starting the in-tervention and at the end of the 8-week program. The assessed variables were: 1) Mindfulness; 2) Emotional Regulation; 3) Attentional Regulation and 4) Behavioral regulation. (3) Results: Chil-dren that participated in both programs, increased their mindfulness and emotional and be-havioral regulation scores. Only children who participated in the program with a focus on at-tention showed significant changes in their ability to self-regulate attention. (4) Conclusions: online MBIs, with attention to external and internal stimuli practices, can be a good strategy to strengthen self-regulation skills of attention, emotions, and behavior in early adolescence.

The consequences of climate change and anthropogenic stressors, such as habitat loss and overexploitation, are threatening the subsistence of species and communities across the planet. Therefore, it is crucial to analyze the impact of environmental perturbations on the diversity, structure and function of ecosystems. In this work, in silico simulations of biodiversity loss were carried out on the marine food web of Caleta Potter (25 de Mayo Island, Antarctica) where global warming has caused critical changes in the abundance and distribution of benthic and pelagic communities during the last 30 years. We performed species removal considering their degree and trophic level and including four different thresholds on the occurrence of secondary extinctions. We examined the impact of extinctions on connectance, modularity and stability of the food web. We found different responses of these properties depending on the extinction criteria used, e.g., large increase in modularity and rapid decrease in stability when most-connected and relatively high-trophic level species were removed. Additionally, we studied the complexity-stability relationship of the food web founding two regimes: 1) high sensitivity to small perturbations suggesting that Potter Cove would be locally unstable, and 2) high persistence to long-range perturbations suggesting global stability of this ecosystem.

Objective: To carry out a bibliometric analysis study of systematic reviews and meta-analyses in dentistry, divided into different thematic areas. Material and method: A search was conducted in the Science Citation Index-Expanded on the core collection of Web of Science, they were selected from the area of Dentistry and Oral Surgery and Medicine categories, the data was downloaded on April 20, 2022 and The 100 most cited articles from each of the thematic areas were selected. Results: An increase in this type of articles was observed in the last decade in the areas of pediatric and medical dentistry and oral pathology. The thematic area that received the most citations was periodontics. The two authors with the most citations are Zwahlen, Marcel and Pjetursson, Bjarni Eluar. The countries that receive the most citations are European, along with the USA and China. The topics that are most published in this type of article deal with Cancer with 50 publications, caries treatment with 25 and fluoridation with 1. The entities that finance this type of articles the most are private companies (26.76%). Conclusions: Together with an exponential increase in the number of publications in dentistry, there has been an increase in the number of publications in systematic reviews. The areas publishing the most articles and having the most citations are Periodontics and Implantology, despite the fact that the most studied topic is cancer.

In this work, an embroidered textile moisture sensor is presented. The sensor is based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidery conductor yarn composed by 99% pure silver plated nylon yarn 140/17 dtex. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 25% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity. Moreover, the reproducibility of the sensor performance subject to the manufacturing process variability and washing process is also evaluated. The results show that the manufacturing variability introduce a moisture measurement error up to 4%. The washing process impact on the sensor behavior after applying the first washing cycle implies a sensitivity reduction higher than 14%. Despite these effect, the textile sensor keeps its functionality and can be reused in standard conditions. Therefore, these properties point out the usefulness of the proposed sensor to develop wearable applications on health and fitness scope including the user needs to have a life cycle longer than one-time use

This review presents an updated overview of research concerning Leishmania protein structures, primarily sourced from the Protein Data Bank (PDB), that play a role in the metabolic pathways of the Leishmania parasite. Furthermore, we assess the current progress in the identification and development of bioactive chemical agents aimed at addressing this substantially overlooked tropical disease. We have analyzed experimental data obtained from in vitro, in vivo and in silico sources. This data has been categorized into four main areas: a) vector taxonomy and geographic distribution; b) parasite taxonomy and geographic distribution; c) enzymatic functions of proteins engaged in parasite/host interactions throughout various developmental stages (such as oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases, and cytokines); and d) established and experimental treatments employing bioactive chemical compounds. Our objective is to establish a foundational point of reference for research efforts concentrating on the elucidation of interaction mechanisms and the processes of ligand-protein activation/inactivation, specifically linked to Leishmania infections. Consequently, we emphasize enzymes recognized for their involvement in the biochemical pathways incited during Leishmania infection episodes. This review encapsulates the current understanding, offering insights to inform and direct future explorations aimed at targeting proteins and pathways to enhance the management of Leishmania-related diseases.

In the present work we propose a dynamical mathematical model of the lung cells inflammation process in response to SARS-CoV-2 infection. In this scenario the main protease Nsp5 enhances the inflammatory process, increasing the levels of NF kB, IL-6, Cox2, and PGE2 with respect to a reference state without the virus. In presence of the virus the translation rates of NF kB and IkB arise to a high constant value, and when the translation rate of IL-6 also increases above the threshold value of 7 pg mL^-1 s^-1 the model predicts a persistent over stimulated immune state with high levels of the cytokine IL-6. Our model shows how such over stimulated immune state becomes autonomous of the signals from other immune cells such as macrophages and lymphocytes, and does not shut down by itself. We also show that in the context of the dynamical model presented here, Dexamethasone or Nimesulide have little effect on such inflammation state of the infected lung cell, and the only form to suppress it is with the inhibition of the activity of the viral protein Nsp5.To that end, our model suggest that drugs like Saquinavir may be useful. In this form, our model suggests that Nsp5 is effectively a central node underlying the severe acute lung inflammation during SARS-CoV-2 infection. The persistent production of IL-6 by lung cells can be one of the causes of the cytokine storm observed in critical patients with COVID19. Nsp5 seems to be the switch to start inflammation, the consequent overproduction of the ACE2 receptor, and an important underlying cause of the most severe cases of COVID19.

Let $a, b$ and $n > 1$ be three positive integers such that $a$ and $\sum_{j=0}^{n-1} b^j$ are relatively prime. In this paper, we prove that the toric ideal $I$ associated to the submonoid of $\mathbb{N}$ generated by $\{\sum_{j=0}^{n-1} b^j\} \cup \{\sum_{j=0}^{n-1} b^j + a\, \sum_{j=0}^{i-2} b^j \mid i = 2, \ldots, n\}$ is determinantal. Moreover, we prove that for $n > 3$, the ideal $I$ has a unique minimal system of generators if and only if $a < b-1$.