Metabolic syndrome is a growing global health problem. Evidence suggests that diets rich in phytochemical-containing herbs and spices can contribute to reduced risk of chronic disease. This review assesses the scope of evidence supporting the use of herbs and spices in the diet for prevention or treatment of metabolic syndrome and associated health conditions. A search of PubMed and Scopus databases was carried out to assess the available clinical or cohort evidence for culinary doses of commonly used herbs and spices. Trials that were measuring health factors related to metabolic disorders or the health of individuals with metabolic syndrome or associated diseases were included. Out of a total of 1742 papers identified, there were 146 relevant studies on black pepper, chilli, cardamom, cinnamon, coriander, cumin, fennel, fenugreek, garlic, ginger, Nigella seed, rosemary, sage and turmeric. No relevant research was found for cloves, mint, oregano, parsley or thyme. Cinnamon, fenugreek and ginger were the herbs/spices with the most published trials on them and showed promise for glycaemic control. Cardamom appears to have potential to reduce inflammatory markers, and cinnamon, ginger and turmeric for blood lipids. Patients with type 2 diabetes were the population most likely to be included in studies, but the preventative benefits of herbs/spices in healthy populations were also investigated, particularly for chilli, ginger and cinnamon. There is evidence for the beneficial effect of culinary doses of many common herbs/spices in the prevention and treatment of metabolic syndrome and associated disorders.

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity and low cost. However, the thorniest issue for wider application of IRT is the quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Carbon Fiber Reinforced Polymer(CFRP) embedded with flat bottom holes were designed via Finite Element Method (FEM) modeling in order to precisely control the depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

Anticipating and planning for the urgent response to large-scale disasters is critical to increase the probability of survival in these events. These incidents present various challenges that complicate the response, such as unfavorable weather conditions, difficulties in accessing affected areas, and the geographical spread of the victims. Furthermore, local socioeconomic factors such as insufficient prevention education, limited disaster assets, and inadequate coordination between public and private emergency services may complicate these situations. In large-scale emergencies, multiple hotspots are usually observed, which requires efforts to coordinate the strategic allocation of human and material resources in different geographical areas. Therefore, the precise management of these resources based on the specific needs of each area becomes fundamental. To address these complexities, this paper proposes a methodology that models these scenarios as an optimization problem, focusing on the location and allocation of resources in mass casualty incidents. The proposed case study is Mexico City in a post-earthquake scenario, using voluntary geographic information, open government data, and historical data from the September 19, 2017 earthquake. Additionally, it is assumed that the resources that require optimal location and allocation are ambulances, which focus on medical issues that affect the survival of victims. The designed solution involves the use of a metaheuristic optimization technique, along with a parameter tuning technique, to find configurations that perform at different instances of the problem, i.e., different hypothetical scenarios that can be used as a reference for future possible situations. Finally, the objective is to present the different solutions graphically, accompanied by relevant information to facilitate the decision-making process of the authorities responsible for the practical implementation of these solutions.

Western countries are experiencing an increasing aging population, resulting in heightened disability and mobility issues. This trend is expected to escalate in the coming decades. Therefore, ensuring adequate accessibility in collective residential housing –where individuals spend much of their daily lives– is of paramount importance. This paper presents a case study focused on the accessibility of building entrances in collective residential housing in Southeast Spain, specifically in the Region of Murcia. In this region, 9.8% of the population has disabilities, and 15.75% were over 64 years old in 2020. The study began by compiling the relevant national and regional accessibility regulations for existing buildings. Subsequently, extensive fieldwork was conducted, analyzing 150 collective residential housing buildings. Based on this analysis, a set of recommendations to enhance accessibility was formulated for buildings not complying with the regulations. The results are presented and discussed in detail. The most frequent recommendation was the construction of accessible ramps, identified as the primary solution in over 40% of cases, either alone or in conjunction with other measures. In 54% of the cases, multiple interventions were necessary to achieve effective accessibility adaptation. The findings of this study could inform the development of public policies aimed at improving accessibility conditions in urban areas.

In the same manner that there are several statements of the second law of thermodynamics but all of them are equivalent, it is possible that most of the entropic methods applied to the nervous system and brain in particular share a similar outcome, or essence, that helps understand some aspects of the fundamentals of basic neurodynamics. In this short review focused on certain aspects of the entropic metrics some results are examined that indicate the fundamental importance of the natural tendency towards a maximal energy distribution for healthy brain activity and thus cognition to emerge.

The saturation properties of symmetric and asymmetric nuclear matter have been computed using the finite range simple effective interaction having Yukawa form-factor. The results of higher order derivatives of the energy per particle and the symmetry energy computed at saturation, namely, Q0, Ksym, Kτ, Qsym, are compared with the corresponding range of values extracted from studies involving theory, experiment and astrophysical observations. The ability of the equations of state computed with this simple effective interaction in predicting the threshold mass for prompt collapse in binary neutron star merger and gravitational redshift have been examined in terms of the compactness of the neutron star and the incompressibility at the central density of the maximum mass star. The correlations existing between neutron star properties with the nuclear matter saturation properties have been analyzed and compared with the predictions of other model calculations.

This note applies the Logistic model approximation to determine the suitable start and end dates for the observed epidemic curves in the total number of cases for different countries. The Logistic model is presented and explicit relations for the beginning and end dates are obtained together with the total epidemic duration. Using data from Brazil, Germany, Italy, and South Korea, the extreme dates are calculated. Since the epidemic onset time is found, a fair comparison of the epidemic curve for these countries is obtained. The result does not depend on the poor statistics available in the early phase of the epidemic when the initial number of infectives is unknown. In fact, the total duration depends only on the characteristic time parameter of the LM model.

The purpose of this project is to develop and build an extensible fixture. This fixture is ideal to milling, drilling, and shaping operations. Jigs and fittings are often the most cost-effective methods of mass fabricating a component. As a result, jigs and fittings are used and play a vital part in the mass production system. These are specialist work holding and tool-guiding devices. The quality of jigs and fixtures used in a process has a substantial impact on its performance. A fixture is distinctive because it is meant to fit a given area or shape. The basic purpose of a fixture is to find and, in certain instances, hold a workpiece throughout an operation. A jig differs from a fixture in that it leads the tool to the right position or movement during an operation, in addition to locating and supporting the workpiece. When a key is reproduced, the original key serves as a base for the path reader, which regulates the tool's movement to construct the duplicate key. In this situation, a CWC machine's route reader works as a jig, with the original being referred to as the template. Sometimes the template and jig refer to the same part of a production system.

Divergences have become a very useful tool for measuring similarity (or dissimilarity) between probability distributions. Depending on the field of application a more appropriate measure may be necessary. In this paper we introduce a family of divergences we call gamma-divergences. They are based on the convexity property of the functions that generate them. We demonstrate that these divergences verify all the usually required properties, and we extend them to weighted probability distribution. We investigate their properties in the context of kernel theory. Finally, we apply our findings to the analysis of simulated and real time series.

In the clinical electrophysiologic practice, the reading and comparing electroencephalographic (EEG) recordings some times is insufficient and take to much time. That is why in the last years it has begun to introduce new methods of EEG analysis, that give a better and faster understanding of the EEG dynamics and allow a rapid intervention in the patient's treatment. Tools coming from the information theory or nonlinear system as an entropy and complexity have been shown to be a very good alternative to address this problem. In this work we introduce a novel method -the permutation Lempel-ziv complexity vs permutation entropy map. This method was applied to EEG of two patients with specific diagnosed pathologies during respective follow up processes of pharmacological changes in order to detect changes that are not evident with the usual inspection method. Our results show that the proposed method are useful for observing an evolutionary retrospective clinical effects of pharmacological interventions in both patients, and from these, to follow the clinical response to the proposed treatment.

Quantum correlations, especially time correlations, are crucial in ghost imaging in order to significantly reduce the background noise on the one hand while increasing the imaging resolution. Moreover, the time correlations serve as a critical reference, distinguishing between signal and noise, which in turn enable clear visualization of biological samples. Quantum imaging also addresses the challenge involved in imaging delicate biological structures with minimal photon exposure and sample damage. Here we explore the recent progress in quantum correlation-based imaging, notably its impact on secure imaging and remote sensing protocols as well as on biological imaging. We also exploit the quantum characteristics of heralded single-photon sources (HSPS) combined with decoy-state methods for secure imaging. This method uses Quantum Key Distribution (QKD) principles to reduce measurement uncertainties and protect data integrity. It is highly effective in low-photon-number regimes for producing high-quality, noise-reduced images. The versatility of decoy-state methods with WCSs (WCS) is also discussed, highlighting their suitability for scenarios requiring higher photon numbers. We emphasize the dual advantages of these techniques: improving image quality through noise reduction and enhancing data security with quantum encryption, suggesting significant potential for quantum imaging in various applications, from delicate biological imaging to secure quantum communication.

A single-crystal of ytterbium-doped “mixed” yttrium-lutetium aluminium garnet with a stoichiometric composition of (Y0.601Lu0.233Yb0.166)3Al5O12 was grown by the Czochralski method and its structure, vibronic, spectroscopic and laser properties were studied. The stimulated-emission cross-section for Yb3+ ions was maximized to 2.53×10-20 cm2 at 1031 nm, the emission bandwidth is ~8 nm and the reabsorption-free luminescence lifetime of the 2F5/2 state is 1.063 ms. Pumped at 941 nm, the Yb-laser generated a maximum output power of 1.04 W at 1.03 and 1.05 μm with a high slope efficiency of 76.4% and a laser threshold of 76 mW. A continuous wavelength tuning over a range of 51.6 nm (1026.4 - 1078.0 nm) was also achieved. Power scaling is achieved using a 969 nm-diode pumped microchip cavity. A maximum output power of ~9 W is obtained at 1.05 μm with a slope efficiency of 76% and with an almost circular laser beam profile.

Our purpose is to address the biological problem of finding foundations of the organization in the collective activity among cell networks in the nervous system, at the meso/macroscale, giving rise to cognition and consciousness. But in doing so, we encounter another problem related to the interpretation of methods to assess the neural interactions and organization of the neurodynamics, because thermodynamic notions, which have precise meaning only under specific conditions, have been widely employed in these studies. The consequence is that apparently contradictory results appear in the literature, but these contradictions diminish upon the considerations of the specific circumstances of each experiment. After clarifying some of these controversial points and surveying some experimental results, we propose that a necessary condition for cognition/consciousness to emerge is to have available enough energy, or cellular activity; and a sufficient condition is the multiplicity of configurations in which cell networks can communicate, resulting in non-uniform energy distribution, the generation and dissipation of energy gradients due to the constant activity. These ideas may reveal possible fundamental principles of brain organization and how healthy activity may derive to pathological states.

One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of “conscious networks” is not exclusive of large brain areas, but can be identified in sub-cellular networks exhibiting non-trivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system’s complexity is maximized, expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.

A large amount of data is produced every day by stakeholders of the Air Traffic Management (ATM) system, in particular airline operators, airports, and air navigation service provider (ANSP). Most data is kept private for many reasons, including commercial and security concerns. More than data, shared information is precious, as it leverages intelligent decision-making support tools designed to smooth daily operations. We present a framework to detect, identify and characterise anomalies in past aircraft trajectory data. It is based on an open source of ADS-B based aircraft trajectories, and extracted information can benefit a wide range of stakeholders: Air Traffic Control (ATC) training centres could play more realistic simulations; ANSP may improve capacity indicators; academics improve safety models and risk estimations; and commercial stakeholders, like airlines and airports, may use such information to improve short-term predictions and optimise their operations. The technique is based on autoencoding artificial neural networks applied on flows of trajectories, which provide a useful reading grid associating cluster analysis with quantified level of abnormality. In particular, we find that the highest anomaly scores correspond to poor weather conditions, whereas anomalies with a lower score relate to ATC tactical actions.

The second external cause of death from unintentional injuries is falls in people over 60, a worldwide public health problem. Associated factors are identified early in Primary Health Care. Thus, we analyze professional narratives about older adults/old age and the organization of services in the presence of fall-inducing frailty. A structured narrative was applied under the following stages: understanding the context; setting/plot/character analysis; and interpretive synthesis. Data were collected from August to November 2022, distributing 21 health professionals in three Narrative Focus Groups. In the analyses, the collective conceptions dialogued with Bourdieu’s Epistemology of field, habitus, and capital. Among the results, technical and common sense representations of older adults were simultaneously observed, along with the belief of old age as a problematic life stage. Care is centered on the installed disease/ailment. Encouraging autonomy and self-care emerges in integrative health practices, which older adults underestimate. Professionals access the lives of older adults according to their habitus, which, in turn, is structured (structuring) in the disputes for installed capital. Thus, the care provided disregards subjectivities and symbolic systems associated with falls.

The purpose of this study is to provide an accurate formula for calculating entropy for short DNA sequences and to demonstrate how to use it to examine leukemia patient surviving. We used IDIBAPS leukemia patient’s data base with 117 anonymized records. The generalized form of the Robust Entropy Estimator (EnRE) for short DNA sequences was proposed and key EnRE futures was showed. The Survival Analysis has been done using statistical package IBM SPSS. Entropy EnRE were calculated for leukemia patients for two samples: A. 2 groups divided by median EnRE and B. 2 groups of patients were formed according to their belonging to 1st and 4th quartiles of EnRE. The result of survival analysis are statistically significant: A. p < 0.05; B. p < 0.005. The death hazard for a patient with EnRE below median is 1.556 times that of a patient with EnRE over median and that the death hazard for a patient of 1st quartile (lowest EnRE) is 2.143 times that of a patient of 4th quartile (highest EnRE). The transition from median to quartile patients’ groups with more EnRE differentiation confirmed the unique significance of the entropy of DNA sequences for leukemia patients surviving.

Aerosol optical depth (AOT) was measured at Xavier University of Louisiana (29.96ᵒ N, 90.11ᵒ W and about 3m above sea level) using a hand-held sun photometer. AOT was measured at two different wavelengths (green at 505nm and red at 625nm) during the period from Sept-2017 to Feb-2018. In this study, we investigate the relationship between AOT and temperature, precipitation, barometric pressure and relative humidity. The maximum monthly average value for green AOT was 0.176 (measured in September) and the minimum monthly value is 0.040 (measured in January). For the red AOT the maximum monthly average value was 0.123 (measured in September) and the minimum is 0.034 (measured in December). The AOT–temperature relationship was predominantly positive, meaning that high AOT values correspond to high temperatures and low AOT values correspond to low temperatures. Relationship between AOT and rainfall is negative, meaning high rainfall averages are associated with low AOT values. AOT and atmospheric pressure have a predominantly negative relationship. The relationship between relative humidity and AOT is a complicated one and is hard to qualify as relative humidity varies very little during the study period.

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

Molecular visualisation is fundamental in the current scientific literature, textbooks and dissemination materials, forming an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Visual exploration has become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. Here we first describe a few Swiss Army knives geared towards protein visualisation for everyday use with an existing large user base, then focus on more specialised tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives.

The absence of interdental papillae leads to the appearance of black triangle. For most patients, the appearance of these triangles is an important reason for concern and affects their social relationships. Multiple reconstruction techniques have been developed with different degrees of success and predictability. The main aim of this study was to evaluate the efficiency of hyaluronic acid (HA) injected into interproximal papillae six months after injection and to perform a systematic review and meta-analysis. After a systematic review, five articles were selected: a clinical randomised controlled trial and four clinical trials. In total, eighty-five patients with a deficiency in upper papillae in the front of the maxilla and jaw were included in the study. The height variable was evaluated (mm) six months after HA injection. In total, one hundred and four interproximal papillae were studied. Three articles showed an important difference in favour of intervention. The total result regarding in the injection of AH was favourable with an approximate average filling of 0.7 mm in the height of the interdental papilla. The injection of HA for the reconstruction of deficient papillae in the region of the upper and lower maxilla was a possible option treatment strategy.

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

Inflammatory Bowel Disease (IBD) presents distinct challenges during pregnancy due to its influence on maternal health and pregnancy outcomes. This literature review aims to dissect the existing scientific evidence on pregnancy in women with IBD and provide evidence-based recommendations for clinical management. A comprehensive search was conducted across scientific databases, selecting clinical studies, systematic reviews, and other pertinent resources. Numerous studies have underscored an increased risk of complications during pregnancy for women with IBD, including preterm birth, low birth weight, neonates small for gestational age, and congenital malformations. Nevertheless, it's evident that proactive disease management before and throughout pregnancy can mitigate these risks. Continuation of IBD treatment during pregnancy and breastfeeding is deemed safe with agents like thiopurines, anti-TNF, vedolizumab, or ustekinumab. However, there's a call for caution when combining treatments due to the heightened risk of severe infections in the first year of life. For small molecules, their use is advised against in both scenarios. Effective disease management, minimizing disease activity, and interdisciplinary care are pivotal in attending to women with IBD. The emphasis is placed on the continual assessment of maternal and infant outcomes and an expressed need for further research to enhance the understanding of the ties between IBD and adverse pregnancy outcomes.

The combination of eco-respectful epoxy compounds with the humins, a by-product of biomass chemical conversion technologies, allow the obtention of materials with high added value. In this work, we propose the chemical connection study of humins with two aliphatic diepoxides through the copolymerization reactions to synthesize sustainable bio-based thermosets. The mechanism insights for the crosslinking between the epoxides and humins was proposed considering the different functionalities of the humins structure. FT-IR spectroscopy, 1 D and 2 D NMR spectroscopy techniques were used to build the proposed mechanism. By these techniques, the principal chain connections and the reactivity of all the components were highlighted in the synthesized networks.

The neocortex is an exquisitely organized structure achieved through complex cellular processes from the generation of neural cells to their integration into cortical circuits after complex migration processes. During this long journey, neural cells need to stablish and release adhesive interactions through cell surface receptors known as cell adhesion molecules (CAMs). Several types of CAMs have been described regulating different aspects of neurodevelopment. Whereas some of them mediate interactions with the extracellular matrix, others allow contacts with additional cells. In this review, we will focus on the role of two important families of cell-cell adhesion molecules (C-CAMs), classical cadherins and nectins, as well as in their effectors, in the control of fundamental processes related with corticogenesis, with especial attention in the cooperative actions among the two families of C-CAMs.

Forensic anthropologists play a key role in skeletal trauma analysis and commonly use macroscopic features to distinguish between trauma types. However, this approach can be challenging, particularly in cases of highly comminuted or incompletely recovered fractures. Histological analysis of microscopic fracture characteristics in fractured bones may thus help provide additional information on trauma type and bone fracture biomechanics in general. This study analysed the extent of microcrack damage to osteons in long bones with blunt force trauma (BFT) and gunshot trauma (GST), from both traumatic death cases and post-mortem experimental fractures. We identified four types of osteonal damage (OD). In traumatic death cases, OD affecting the inside of the osteon and compromising the Haversian canal (type 1) was found to be indicative of BFT. Moreover, OD affecting the cement line (type 3) and interstitial lamellae (type 4) was more common in the GST samples. OD affecting the inside of the osteon without compromising the Haversian canal (type 2) was not found to be indicative of either trauma type. In cases of experimental fractures, our study revealed that post-mortem fractures in dry bone samples featured the highest amount of OD, particularly of type 4. This study also found that the experimentally produced GST featured similar OD pattern to GST death cases. These findings support our hypothesis that there are distinct osteonal damage patterns in human long bones with BFT and GST, which are of relevant value for trauma analysis in forensic anthropology.

Background: Diabetes mellitus (DM) and periodontitis are two chronic diseases that are interconnected. The coexistence of these conditions leads to increased severity of periodontitis and challenges in controlling blood glucose levels in diabetic patients. Objectives: The aim of this study was to evaluate both the influence of periodontal disease and its treatment in patients with DM in terms of a reduction in glycosylated hemoglobin levels at 3 and 6 months after treatment. Methods: A sequential, nonprobabilistic, controlled, prospective and longitudinal case−control study was carried out at the University Dental Clinic of the Morales Meseguer Hospital in Murcia, Spain. Thirty diabetic patients were divided into two groups: patients with periodontitis (test group) and patients without periodontitis (control group). The periodontal and endocrine-metabolic variables were measured at baseline and at 3 and 6 months after periodontal treatment for both groups. Results: Statistically significant differences were found at 3 and 6 months after periodontal treatment with respect to HbA1c levels in the group of periodontal patients. However, these differences were not observed in the control group. Conclusion: The presence of periodontal disease increased HbA1c levels in patients with DM. Nonsurgical periodontal treatment significantly decreased the degree of periodontal inflammation and the HbA1c level at 3 and 6 months after treatment.

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity, and low cost. However, the thorniest issue for the wider application of IRT is quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Finite Element Method (FEM) modeling provides the economic examination of the response pulsed thermography. In this work, Carbon Fiber Reinforced Polymer (CFRP) specimens embedded with flat bottom holes are stimulated by a FEM modeling (COMSOL) with precisely controlled depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the stimulated CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

Variations in geochemical signatures of fossil brachiopod shells may be due to diagenesis and/or biological processes (i.e. ‘vital effects’). Characterize them is crucial to identify reliable areas into the shell suitable to paleoclimatological studies. This investigation contributes to an in-depth understanding of geochemical variations of Gigantoproductus sp. shells (SW Spain, Serpukhovian age), which could affect to the Late Paleozoic Ice Age interpretation. Microstructural, crystallographic, cathodoluminescence and geochemical (minor and trace elements, δ18O, δ13C, and strontium isotopes) characterisation have been performed on the tertiary layer of the ventral valve, to assess the preservation state. Poorly-preserved areas exhibit microstructural and geochemical changes such as recrystallisation, fracturing and higher Mn and Fe enrichment. Moreover, these areas have higher dispersion of ⁸⁶Sr, ⁸⁷Sr, δ18O and δ13C than well-preserved areas. Three structural regions have been identified in well-preserved areas of ventral valve by differences in valve curvature and thickness, such as the umbonal, thick and thin regions. These regions have different proportions of Mg, S, Na, δ18O, and δ13C, whom are interpreted as ‘vital effects’ and probably are related with growth rate differences during shell growth. Gigantoproductus tertiary layer seems the best suitable to paleoclimatological studies because it retains the original microstructure and geochemistry.

As climate change should lead to an increase in the vulnerability and the sensitivity of forests to extreme climatic events, quantifying and predicting their response to more severe droughts remains a key task for foresters. Furthermore, recent works have suggested that tree diversity may affect forest ecosystem functioning, including their response to extreme events. In this study we aimed at testing whether the growth response of forest stands to stressful climatic events varied between mixed and monospecific stands, under various environmental conditions. We focused on beech-fir forests (Fagus sylvatica [L.] and Abies alba [L.]) and beech-oak forests (Fagus sylvatica [L.] and Quercus pubescent [L.]) in the French Alps. We used a dendrochronological dataset sampled in forest plots organized by triplets (one mixture and two monospecific stands) distributed in six sites along a latitudinal gradient. We tested (1) whether stand diversity (two-species stands vs monospecific stands) modulates the stands’ response to drought events in terms of productivity, (2) whether species identity may drive the diversity effect on resistance and recovery, and (3) whether this can be explained by interspecific interactions. We found that (1) interspecific differences in response to extreme drought events (possibly due to interspecific differences in hydraulic characteristics) can induce a mixture effect on stand growth, although it appeared (2) to be strongly depending on species identity (positive effect only found for beech-fir mixed stands), while (3) there were no significant non-additive effects of diversity on stand resistance and recovery, except for some specific cases. Overall, our study shows that promoting selected mixed stands management may buffer extrem drought effect on stand productivity.

The resolution of façade construction is not considered in the design process, as it can be expressed by complex technological innovations that emphasize the beauty of buildings. Nevertheless, resorting to this type of technology solution may not always be necessary. This study demonstrates this hypothesis through the investigation of five iconic case studies emphasizing the construction system analysis and the revelation of the brainwave idea. The brainwave idea defines the construction innovation that enables the detail by simplification rather than sophistication. Notable, unlike complex technological innovation, standard systems or elements applied strategically are considered little innovations to facilitate the resolutions of the façade complexity. Many of these innovations occur during the visual and constructive prototype progress required to validate the proposed solution and its performance. Therefore, real-scale prototype development that operates as a real-scale laboratory is necessary to correct and validate successive solutions.

Overcrowding in the emergency department is a problem that generates several implications for bed management, which is deemed one of a hospital's most critical processes. Effective management of hospital production capacity includes bed management processes, which can be improved in order to leverage hospital performance. Thus, this study sought to understand how bed management works and identify the main factors that influence its management. The study was performed through a case study, with data collected from semi-structured interviews and bibliographic research, which were triangulated. Thematic content analysis of the interviews and cross-analysis were performed. As a result, the main factors that influence hospital Bed management were identified: communication between teams and units; definition of performance goals; decisions shared between units; occupation and discharge planning by the teams; length of stay; the role of the nurses; and COVID-19. The greatest difficulties in the management process are related to these factors. Additionally, suggestions are provided to mitigate such reported difficulties.

In Cameroon, alcoholic beverages remain the main consumed drink. In the Northern regions, indigenous sorghum beers are popular and widely consumed in an actively fermenting state by the people. In this study, some physicochemical parameters of the alcoholic sorghum beverages and correlations between them were evaluated during fermentation for 10 days. The indigenous white and red beers were produced at the laboratory scale assisted by experimented producers and some parameters (pH, total acidity, alcohol, sugars, density, total solids, temperature, and conductivity) were measured on the wort and fermented beverages. The pH decreases from 3.2 to 2.4 and 3.11 to 2.41; total acidity increases from 1.07 to 5.1 g/l and 0.5 to 4.6 g/l; alcohol enhances from 0 to 9.5% and 0 to 6.8% (v/v); total solids drop from 13.6 to 5°P and 12.2 to 3.3°P were observed respectively in the white and red sorghum beers. The multivariate analysis showed a good correlation between consumption of sugar, the decrease of total solids and density with the decrease in pH. It was also shown that, a perfect link exist between the production of alcohol and organic acids. The hierarchical analysis showed that indigenous red beer samples fermented for 1 and 2 days and those fermented for 4 to 10 days are related and could be separate in two distinct groups, whereas white turbid beer samples are separated in three different groups, those fermented for 1 to 4 days, those 5 to 6 days and those 7 to 10 days. The results obtained could serve as a guide to better understand the fermentation process of the indigenous alcoholic sorghum-based beverages.

Additive manufacturing (3D printing) and computer-aided design (CAD) still have limited up-take in biomedical and bioengineering research and education, despite the significant potential of these technologies. The utility of organ-scale 3D-printed models of living structures is widely appreciated, while the workflows for microscopy data translation into tactile-accessible replicas are not well developed yet. Here, we demonstrate an accessible and reproducible CAD-based methodology for generating 3D-printed scalable models of human cells cultured in vitro and imaged using conventional scanning confocal microscopy and fused deposition modelling (FDM) 3D printing. We termed this technology CiTo-3DP (Cells-in-Touch for 3D Printing). As a proof-of-concept, we created CiTo-3DP models of human pancreatic cancer cells and healthy dermal fibroblasts by using selectively stained nuclei and the cytoskeleton components (f-actin and α-smooth muscle actin). The production of dismountable sets of cellular components was al-so shown. The CiTo-3DP approach can be adapted to comprehensively present various cell types, subcellular structures and extracellular matrices. We envisage that the resulting CAD and 3D printed models could be used for further applications, including but not limited to in silico simulations for biology, medicine, pharmacological research, tissue engineering, morphometrical analysis, multiphysics modelling, education, rehabilitation of visually impaired people, and integration into virtual reality.

Defensive behavior is a function of specific survival circuits, the “aversive brain system”, that are thought to be conserved across vertebrates, and involve threat detection and the organization of defensive responses to reduce or eliminate threat. In mammals, these circuits involve amygdalar and hypothalamic subnuclei and midbrain circuits. The increased interest in teleost fishes as model organisms in neuroscience created a demand to understand which brain circuits are involved in defensive behavior. Telencephalic and habenular circuits represent a “forebrain circuit” for threat processing and organization of responses, being important to mounting appropriate coping responses. Specific hypothalamic circuits organize neuroendocrine and neurovegetative outputs, but are the less well-studied in fish. A “midbrain circuit” is represented by projections to interneurons in the optic tectum which mediate fast escape responses via projections to the central gray and/or the brainstem escape network. Threatening stimuli (especially visual stimuli) can bypass the “high road” and directly activate this system, initiating escape responses. Increased attention to these circuits in an evolutionary framework is still needed.

Since it was proposed, the Robot Operating System (ROS) has fostered solutions for various problems in robotics in the form of ROS packages. One of these problems is Simultaneous Localization and Mapping (SLAM), a problem solved by computing the robot pose and a map of its environment of operation at the same time. The increasingly availability of robot kits ready to be programmed and also of RGB-D sensors often pose the question of which SLAM package should be used given the application requirements. When the SLAM subsystem must deliver estimates for robot navigation, as is the case of applications involving autonomous navigation, this question is even more relevant. This work introduces an experimental analysis of GMapping and RTAB-Map, two ROS compatible SLAM packages, regarding their SLAM accuracy, quality of produced maps and use of produced maps in navigation tasks. Our analysis aims ground robots equipped with RGB-D sensors for indoor environments and is supported by experiments conducted on datasets from simulation, benchmarks and from our own robot.

The research paper investigates the synthesis of metal matrix composites (MMCs) through the amalgamation of aluminum and silicon carbide particles, employing a two-step mixing methodology called the stir casting method. Metal matrix composites are materials that enhance the capabilities of a metallic matrix by incorporating another material. This leads to better characteristics such as tensile and shear moduli, fatigue and fracture properties, thermal expansion coefficient, and more. Aluminum-matrix composites are a class of materials that possess distinct characteristics that may be modified by altering factors such as the type of reinforcing material, the amount of reinforcement, and the fabrication technique employed to produce the composite. The concept aims to combine the desirable properties of metals and ceramics by incorporating durable refractory particles into a malleable metal structure. The fabrication process employs the stir casting technique, where reinforcing phases are mechanically stirred into a molten matrix to create cast composites with reinforcement volume percentages of up to 30%. The study utilizes Response Surface Methodology to enhance the mechanical properties of the composites through the optimization of manufacturing parameters, including stirring temperature, time, and speed. The study entails analyzing the correlation between different casting conditions and the resulting changes in hardness and tensile strength.

Many applications in the context of Industry 4.0 require precise localization. However, indoor localization remains an open problem, especially in complex environments such as industrial environments. In recent years, we have seen the emergence of Ultra WideBand (UWB) localization systems. The aim of this article is to evaluate the performance of a UWB system to estimate the position of a person moving in an indoor environment. To do so, we implemented an experimental protocol to evaluate the accuracy of the UWB system both statically and dynamically. The UWB system is compared to a ground truth obtained by a motion capture system with a millimetric accuracy.

The number of documents published on the Web other languages than English grows every year. As a consequence, it increases the necessity of extracting useful information from different languages, pointing out the importance of researching Open Information Extraction (OIE) techniques. Different OIE methods have been dealing with features from a unique language. On the other hand, few approaches tackle multilingual aspects. In such approaches, multilingual is only treated as an extraction method, which results in low precision due to the use of general rules. Multilingual methods have been applied to a vast amount of problems in Natural Language Processing achieving satisfactory results and demonstrating that knowledge acquisition for a language can be transferred to other languages to improve the quality of the facts extracted. We state that a multilingual approach can enhance OIE methods, being ideal to evaluate and compare OIE systems, and as a consequence, to applying it to the collected facts. In this work, we discuss how the transfer knowledge between languages can increase the acquisition from multilingual approaches. We provide a roadmap of the Multilingual Open IE area concerning the state of the art studies. Additionally, we evaluate the transfer of knowledge to improve the quality of the facts extracted in each language. Moreover, we discuss the importance of a parallel corpus to evaluate and compare multilingual systems.

The 70/30 copper–nickel alloy is mainly used in critical parts with more demanding conditions in marine settings. There is a need for innovative methods that offer fast production and cost-effectiveness to supplement current copper–nickel alloy manufacturing processes. In this study, we employ wire-arc additive manufacturing (WAAM) to fabricate the 70/30 copper–nickel alloy. The as-built microstructure is characterized by columnar grains with prominent dendrites and chemical segregation in the inter-dendritic area. The aspect ratio of the columnar grain increases with increasing travel speed (TS) at the same wire feed speed (WFS). This is in contrast to an equiaxed grain structure with a more random orientation of conventional sample. The sample built with a WFS of 8 m/min, TS of 1000 mm/min, and a track distance of 3.85 mm exhibits superior corrosion properties in the 3.5 wt% NaCl solution compared to the conventional one, as evidenced by a higher film resistance and breakdown potential, along with a lower passive current density of the WAAM sample. The corrosion morphology reveals the critical roles played by the nickel element unevenly distributed between the dendrite core and inter-dendritic area.

Phosphorus (P) is a vital macronutrient crucial for crop productivity. Plants absorb P salts, mainly orthophosphate, from soil, yet the primary P source resides in organic materials. Soil phosphomonoesterases (APases) play a vital role in releasing P from organics via hydrolysis. Acid and alkaline phosphatases are crucial for alleviating P deficiency in plants. In this review focused on agricultural soils, we studied the relationship of biophysicochemical, agricultural management, and climate factors on APases also its connection with crop growth and yields. Our findings indicate a strong linkage between both APases and soil pH, positively influenced by clay content, organic matter, microbial biomass carbon, and nitrogen. Adopting healthy soil practices like balanced organic fertilizer usage, optimal soil water levels, reduced tillage, crop rotation, and using beneficial plant microbes help boost APase activity. However, the connection between APases and crop productivity remains uncertain due to insufficient research in this area. Our review emphasizes the vital need to evaluate the relationship between APases and meso-macrofauna, alongside essential plant nutrients such as potassium, nutrient ratios, and the synergistic effects of various factors. Understanding the rapid, efficient assimilation of P through APases in the plant-soil and/or plant-microbiota ecosystem it can be crucial for crop productivity and yields.

The so-called Born-Huang ansatz is a fundamental tool in the context of ab-initio molecular dynamics, viz., it allows to effectively separate fast and slow degrees of freedom and thus treating electrons and nuclei at different mathematical footings. Here we consider the use of a Born-Huang-like expansion of the three-dimensional time-dependent Schr\"odinger equation to separate transport and confinement degrees of freedom in electron transport problems that involve geometrical constrictions. The resulting scheme consists of an eigenstate problem for the confinement degrees of freedom (in the transverse direction) whose solution constitutes the input for the propagation of a set of coupled one-dimensional equations of motion for the transport degree of freedom (in the longitudinal direction). This technique achieves quantitative accuracy using an order less computational resources than the full dimensional simulation for a prototypical two-dimensional constriction.

Anomaly detection is an active area of research with numerous methods and applications. This survey reviews the state-of-the-art of data-driven anomaly detection techniques and their application to the the aviation domain. After a brief introduction to the main traditional data-driven methods for anomaly detection, we review the recent advances in the area of neural networks, deep learning and temporal-logic based learning. We cover especially unsupervised techniques applicable to time series data because of their relevance to the aviation domain, where the lack of labeled data is the most usual case, and the nature of flight trajectories and sensor data is sequential, or temporal. The advantages and disadvantages of each method are presented in terms of computational efficiency and detection efficacy. The second part of the survey explores the application of anomaly detection techniques to aviation and their contributions to the improvement of the safety and performance of flight operations and aviation systems. As far as we know, some of the presented methods have not yet found an application in the aviation domain. We review applications ranging from the identification of significant operational events in air traffic operations to the prediction of potential aviation system failures for predictive maintenance.

The corrosion behavior of Fe-containing directionally solidified (DS) and centrifugally cast (CC) Al-Si-Cu-Zn alloys with either Co or Ni additions has been investigated. Electrochemical and immersion corrosion methods were used to investigate the corrosion behavior in 0.6 M NaCl after short (1-hour) and long (30-day) exposure periods. The employed solidification methods allowed the production of samples with a wide range of secondary dendrite arm spacing (SDAS) while preserving Si and Fe-containing phases. The 0.5 wt.% Ni and Co additions led to the growth of the AlFeSi(Ni) and AlFeSi(Co) phases, but no binary AlNi nor AlCo intermetallic par-ticles have been generated. Potentiodynamic polarization studies at early exposure revealed an increase in the corrosion potential as the Ni was added for either fast or slow solidified samples. The electrochemical impedance spectroscopy at early exposure demonstrated that the Ni-modified alloy, on the other hand, was associated to smaller charge transfer resistances, in-dicating a reduction in corrosion resistance after short elapsed time into the electrolyte. Howev-er, 30-day immersion tests revealed much lower corrosion rate of the Ni-modified alloy than the other alloys, while the corrosion rates of the Co-modified and non-modified alloys were simi-lar. In the Ni-containing alloy, decreased corrosion rate under long-term corrosion process was attributed to the formation of a thick and dense alumina layer, effectively protecting the surface under such conditions. This work contributes to a better knowledge of the corrosion behavior of Ni- and Co-corrected Al industrial scrap compositions.

Graphene-based Field-Effect Transistors (FETs) integrated with microstrip patch antennas offer a promising approach for Terahertz signal radiation. In this study, a dual-stage simulation methodology is employed to comprehensively investigate the device’s performance. The initial stage, executed in MATLAB, delves into charge transport dynamics within a FET under asymmetric boundary conditions, employing hydrodynamic equations for electron transport in the graphene channel. Electromagnetic field interactions are modeled via Finite-Difference Time-Domain (FDTD) techniques. The second stage, conducted in COMSOL Multiphysics, focuses on the microstrip patch antenna’s radiative characteristics. Notably, analysis of the S11 curve reveals minimal reflections at the FET’s resonant frequency of 1.34672 THz, indicating efficient impedance matching. Examination of the radiation pattern demonstrates the antenna’s favorable directional properties. This research underscores the potential of graphene-based FETs for Terahertz applications, offering tunable impedance matching and high radiation efficiency for future Terahertz devices.

The relative proportions between nutrients affects the fate of them for metabolic interconversion, storage and turnover or, essentially for energy, in a process of partition modulated by hormonal and metabolic factors. A basic common chow model was used: ST or standard diet, HF high-fat and HP or high-protein had a common substrate. A CF cafeteria-type diet was added for comparison. Rats (female and male) received the diet for 30d. Nutrient intake and body composition were measured. Plasma glucose, lactate, testosterone (T) and estradiol (E2) were measured. Common groups energy intake, was largely based in carbohydrates CH, yielding 6C units, which were fully oxidized or stored as 2C fragments (fatty acids). Lactate (3C) was partially stored as glycerol of TAG. Accrual of 2C far exceeded about ten-fold that of 3C. Amino acid (AA) catabolism yielded 2C, 3C and 4C-5C fragments, the latter acting as Krebs cycle anaplerotic intermediates (KCAI), that facilitated the oxidation of 2C in detriment of TAG accumulation Lactate levels, were related to lactic dehydrogenase activities in muscle and liver. TAG accrual was maximal in CF, quite differently from HF with similar diet lipid proportion. Maximal rates of lipid storage were found in ST (and CF) groups. Females showed a higher ability to oxidize CH and to store less TAG. T increased N and protein deposition, whilst E2 decreased them favoring AA oxidation and the availability of KCAI. In the rat, an effective energy partition scheme requires that about half of the energy is provided by CH (polysaccharide), and needs enough protein to provide KCAI for a smooth 2C oxidation.

Animal welfare assessment protocols are important for identifying welfare problems in conservation programs. This study aimed to develop a baseline welfare protocol for the assessment of welfare in huemul (Hippocamelus bisulcus) in conservation centers. This protocol is based on the Welfare Quality® (WQ) framework for cattle, considering the available literature on the behaviours, ecology, conservation plans, captive management of this species, and welfare assessment protocols for other ungulate species. As a result, the protocol was specifically developed for huemuls and included four principles, 12 criteria, and 23 animal- and resource-based indicators. The 12 criteria of the WQ protocol were reduced to nine, and three new criteria were added because they were both feasible and essential for welfare assessment in captive huemuls. This protocol is mainly intended to identify welfare problems in endangered species in the context of conservation centers (reproduction, rescue, rehabilitation, or treatment centers). Thus, aggregation of different measures to obtain a global score has not been proposed. However, a scoring system that assigns a value on a 0-2 scale (0= No welfare concern; 1= welfare concern; 2= urgent welfare concern) is proposed for each category. Although further research is still needed to fully validate the protocol, this is the first development of a completed protocol for huemul welfare assessment.

Friction stir welding (FSW) is a solid state welding process for joining metallic alloys and dissimilar metals. It has emerged as an alternative technology for welding high strength alloys that are difficult to join with conventional techniques. FSW is used to produce products with better mechanical properties. Now a days aluminum alloys have been widely used in several industrial applications such as aerospace, marine, automobile and commercial applications due to their light weight structure, better mechanical properties and high corrosion resistance.In this work, three welding parameters such as spindle speed, welding speed and plunge depth were considered for friction stir welding. FSW was carried out between dissimilar aluminum alloy plates (AA6061 and AA 8011) to produce butt joint.A Box-Behnken design with three factors and three levels was chosen to minimize the number of experimental conditions .The tensile strength and hardness of the welded regions were evaluated. The optimum level settings and the major parameters that influence the joint strength were obtained by Box-Behnken design.

In this paper, we analyze data from the 2012 Encuesta de Integración Social y Salud (Social Integration and Health Survey) of the Instituto Nacional de Estadística (Spanish National Institute of Statistics) to obtain profiles created by combining disability, poverty and social exclusion. We hypothesize that the probability that people will experience social exclusion increases if they have a disability, chronic illness or limitation in conducting everyday activities, and that this probability is greater for women than for men. To conduct our analysis, we constructed a social exclusion model based on a series of social determinants that acts as a dependent variable. In this context, social exclusion is understood to go beyond the concept of financial poverty. We performed bivariate analyses, in which we calculated the Odds Ratios (OR) for certain variables considered to be predictors of social exclusion. We also performed a means comparison test and an ANOVA test to observe differences between individuals with recognized disability and those without. Finally, we conducted logistic regression analysis to determine which vulnerability profiles are most likely to experience a situation of social exclusion. We also discuss the limitations of our study, and suggest areas in, which the relationships between health, social exclusion and disability can be further investigated.

This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, con-tingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Excessive or insufficient ERK activity inhibits growth, whereas moderated activation supports proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.

Single Image Super Resolution (SSIR) is a problem in computer vision where the goal is 1 to create high-resolution images from low-resolution ones. It has important applications in fields 2 such as medical imaging and security surveillance. While traditional methods such as interpolation 3 and reconstruction-based models have been used in the past, deep learning techniques have recently 4 gained attention due to their superior performance and computational efficiency. This article proposes 5 an Autoencoder based Deep Learning Model for SSIR, in particular, a light model that uses fewer 6 parameters without compromising performance. The down-sampling part of the Autoencoder 7 mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose 8 convolution and residual connections from the down sampling part. The model is trained using a 9 subset of the VILRC ImageNet database. The model is evaluated using quantitative metrics PSNR, 10 SSIM as well as qualitative measures such as perceptual quality. PSNR and SSIM figures as high as 11 76.06 and 0.93 are reported.

Adaptive mechanisms, such as channel hopping and packet replication, are used in low-power wireless networks to deal with the spatial and temporal variations in the link quality, and meet the reliability requirements of industrial applications (i.e., PDR>99%). However, the benefits of such mechanisms are limited and may have a large impact on end-to-end latency and energy consumption. Hence, in this paper we propose using adaptive modulation diversity, which allows to dynamically select different modulations, to improve link reliability. We present three adaptive modulation diversity selection strategies and validate them using the data derived from a real-world deployment using the IEEE 802.15.4g SUN modulations (i.e., SUN-FSK, SUN-OQPSK and SUN-ODFM) in an industrial environment. The results show that by using adaptive modulation diversity it is possible to improve link reliability regardless of node conditions.

The adoption of harmful postures due to a sedentary lifestyle, which involves long periods at work in offices, is a factor that exacerbates musculoskeletal risks. To examine these risks, there are numerous postures analysis methods, such as Rapid Upper Limb Assessment (RULA) and Rapid Office Strain Assessment (ROSA). RULA is a consolidated method to evaluate the exposure of individual workers to ergonomic risk factors associated with upper extremity musculoskeletal disorders. In turn, ROSA is a more recent method that quantifies exposure to risk factors in an office work environment. This research aims to identify whether there is harmony between these two methods, ROSA and RULA. Through applied research, from a qualitative perspective, the scientific procedures adopted were direct observation and ROSA and RULA postural assessment instruments. The study was conducted in the radiology service and focused on the outpatient reception workstation. Results indicated that further investigation must occur to make working conditions changes as soon as possible and that both methods are harmonic. As contributions of the analysis, we have discussed the working conditions and suggested improvements to reduce the risks of musculoskeletal morbidity symptoms. We recommend future studies aimed at measuring the levels of complementarity between these methods by quantitative approaches.

1) Background: It has been more than a decade since the concern about addictive use of the Internet and mobile phones was first expressed and its possible inclusion into the lists of mental disorders has been a popular topic of discussion recently, thus it seems to be a fitting moment to investigate the evolution of this issue over time. The aim of the present study was to analyze the evolution of the perception of problematic Internet and smartphone use in young people over the period 2006–2017; 2) Methods: To this end, a questionnaire on Internet use habits and the CERI and CERM questionnaires on negative consequences of Internet and smartphone use were administered to a sample of 792 university students and compared with data from former studies over the period 2006–2017; 3) Results: The perception of problematic Internet and mobile phone use has increased over the last decade, social networks are considered responsible for this increase, and females are the ones perceived to be more affected than males. The degree to which participants agree with the statement “I am addicted to the Internet” can be used as a screening item for problematic use.

The vehicular ad hoc network (VANET) when augmented with internet is called internet of vehicles (IoV). In the IoV, vehicles have on board units (OBUs), use communication technologies and customized software to communicate with infrastructure around them. The vehicles can have permanent connectivity and global network awareness based on cloud computing. IoV technologies are still being assessed to ensure that the network is protected from attacks, supports a dynamic vehicular mobility scenarios and meets the low latency communication requirements between the vehicles and the surrounding infrastructure. To meet these strict Quality of Service (QoS) demands, Unmanned Aerial Vehicles (UAVs) play a vital role in IoV ecosystems. An UAV can serve as a mobile roadside unit (mRSU) to transmit data between vehicles, stationery RSUs and other UAVs. The UAVs have better line of sight (LOS) connections which result in better channel states and lower path loss than fixed RSUs. Although the inclusion of UAVs in vehicular networks has improved the system performance by providing better resource management and routing solutions, the traditional optimization techniques with their limitations are often not applicable. Therefore, in recent years, research community is integrating Artificial Intelligence (AI) and Machine Learning (ML) into UAV based IoV ecosystem to better manage resource allocation, routing and mobility management issues to optimize the overall network performance. In this survey paper we review the existing research done in AI/ML based UAV-IoV networks and communications with focus on resource management and routing from year 2019 to 2023. We have studied different AI techniques, their training attributes and architectures in various research works. The limitations of AI-based approaches in terms of required computational resources, availability of real world data and AI models’ complexity for the UAV-IoV environment are also discussed. Finally, the future directions for UAV-IoV research opportunities that can leverage the full potential of AI are presented.

In the context of freshwater ecosystems, turbidity and suspended solids play crucial roles, with their levels significantly influenced by anthropogenic activities. This study focuses on assessing and monitoring these parameters in Albufera de Valencia using Sentinel-2 imagery. The primary aim is to establish reliable estimation algorithms that can contribute to effective ecosystem management. The study calibrated and validated algorithms for estimating turbidity and suspended solids. The R783×R705/R490 model proved to have the best performance for estimating turbidity and total solids in the Albufera. However, R783/R490 obtained a higher coefficient of de-termination for the organic part, while the R705 band was selected for the inorganic part. However, to achieve better estimates of turbidity and inorganic matter, more research is needed in the future. The implications of excessive suspended solids are underscored, including the depletion of dissolved oxygen, and reduced primary productivity due to limited light penetration and habitat availability. Collaboration between disciplines such as limnology, optics and water chemistry are crucial to advance water quality estimation models in lakes and lagoons such as Albufera. By integrating expertise and approaches from these diverse fields, new knowledge can be gained and the basis for more effective management and conservation strategies can be laid.

Deformation flows are flows incorporating shear, strain and rotational components. These flows are ubiquitous in the geophysical flows, such as the ocean and atmosphere. They appear near almost any salience, such as isolated coherent structures (vortices and jets), various fixed obstacles (submerged obstacles, continental boundaries). Fluid structures subject to such deformation flows may exhibit drastic changes in motion. In this review paper, we focus on the motion of a small number of coherent vortices embedded in deformation flows. Problems involving isolated one and two vortices are addressed. When considering a single-vortex problem, the main focus is on the evolution of the vortex boundary and its influence on the passive scalar motion. Two vortex problems are addressed with the use of point vortex models, and the resulting stirring patterns of neighbouring scalars are studied by a combination of numerical and analytical methods from the dynamical system theory. Many dynamical effects are reviewed with emphasis on the emergence of chaotic motion of the vortex phase trajectories and the scalars in their immediate vicinity.

Renewable energy sources are increasingly crucial for meeting global energy demands in an eco-friendly manner, particularly as the world shifts away from fossil fuels and faces higher volatility of the market prices. Portugal, a country with limited fossil fuel reserves and high energy dependency, has heavily invested in renewables in recent years. However, renewables like sunlight, wind, and water are inherently unsteady due to climate influences, resulting in energy production fluctuations. To mitigate this issue, energy storage systems are being deployed to stabilize renewable energy supply during production lulls. This project aims to assess an energy storage system and define technical specification in order to maximize profitability at the Finerge-owned Alto Douro wind farm. To achieve this, we've conducted an energy demand analysis, followed by simulations to assess system performance in relation to energy use and profit, while varying parameters such as power and efficiency. We've also compared commercial proposals from different battery manufacturers utilizing various technologies. Our findings suggest that high-power, quick charge-discharge lithium-ion batteries are the most suitable solution, given their efficiency and modularity. These attributes are vital for achieving current and future profitability.

Background: Traditional omic analysis relies on p-value and fold change as selection criteria. There is an ongoing debate on their effectiveness in delivering systemic and robust interpretation, due to their dependence on assumptions of conformity with various parametric distributions.Here, we propose a threshold-free selection method based on robust, non-parametric statistics, ensuring independence from the statistical distribution properties and broad applicability. Such methods could adapt to different initial data distributions, contrary to statistical techniques based on fixed thresholds. Methods: Our work extends the Rank Products methodology with a neutral selection method of high information-extraction capacity. We introduce the calculation of the RP distribution’s entropy to isolate the features of interest by their contribution to the distribution’s information content. The aim is a methodology performing threshold-free identification of the differentially expressed features, which are highly informative about the phenomenon under scrutiny. Conclusions: Applying the proposed method on microarray (transcriptomic and DNA methylation) and RNAseq count data of varying sizes and noise presence, we observe robust convergence for the different parameterisations to stable cutoff points. Functional analysis through BioInfoMiner and EnrichR was used to evaluate the information potency of the resulting feature lists. Overall, the derived functional terms provide a systemic description highly compatible with the results of traditional statistical hypothesis testing techniques. The methodology behaves consistently across different data types. The feature lists are compact and information-rich, indicating phenotypic aspects specific to the tissue and biological phenomenon i nvestigated. Selection by information content measures efficiently addresses problems, emerging from arbitrary thresholding, thus facilitating the full automation of the analysis.

Pulsed thermography is a vital technique in the nondestructive evaluation field. However, its data analysis can be complex and requires skilled experts. Advances in deep learning have yielded exceptional results, including image segmentation. Therefore, many efforts have been made to apply deep learning methods to data processing for nondestructive evaluation. Despite this, there is currently no public Pulsed thermographic dataset available for evaluating various spatial-temporal deep methods of segmenting pulsed thermographic data. This article aims to provide such a dataset and assess the performance of commonly used deep learning-based instance segmentation models on it. Additionally, the impact of the number of frames and data transformations on model performance is examined. The findings suggest that suitable preprocessing methods can effectively reduce the data size without compromising the deep models’ performance.

Inland capture fisheries play a critical role in supporting food security and livelihoods in West Africa. Therefore, it is important to evaluate genetic health of exploited fish populations. The African bonytongue, Heterotis niloticus, supports important commercial and subsistence fisheries in West Africa. Sharp declines of stocks have been reported, however. Herein, we estimate contemporary effective population sizes (Ne) of four Heterotis populations in Nigeria, three in Benin, and five in Cameroon using the Linkage Disequilibrium method with correction for age structure. Ne estimates were used to assess genetic short-term (i.e., inbreeding depression) and long-term (i.e., loss of evolutionary potential) risks. Analyses failed to obtain Ne point estimates for two populations. For the remaining ten populations, corrected Ne point estimates fell well below 500, the minimum recommended for populations to retain evolutionary potential; with eight populations below 100 (range 2.8–83.5), the minimum recommended to avoid inbreeding depression, one borderline (100–125), and one above this threshold (312–392). The lower 95% confidence interval bound of Ne for eleven populations was very small (0.7–14.6), and for the remaining population it was 44.2. Accordingly, all populations examined can be considered potentially at risk of inbreeding depression.

Methane and carbon dioxide are the main contributors to global warming, being the methane effect twenty-five times more powerful than carbon dioxide. Although the sources of methane are diverse, it is a very volatile and explosive gas. One way to store the energy content of methane is its conversion to methanol. Methanol is liquid under ambient conditions, easy to transport and, apart from its use as an energy source, it is a chemical platform that can serve as a starting material for the production of various higher value-added products. Accordingly, the transformation of methane to methanol has been extensively treated in the literature, using traditional catalysts as different types of zeolites. However, in the last years, a new generation of catalysts have emerged to carry out this transformation with higher conversion and selectivity, and more importantly, under mild temperature and pressure conditions. These new catalysts typically involve the use of a highly porous supporting material such as zeolite, or more recently, metal-organic frameworks (MOFs) and graphene, and metallic nanoparticles or a combination of different types of nanoparticles that are the core of the catalytic process. In this review, the characteristics, the catalytic mechanisms, reactors, and the main results of these catalysts are presented as a way to overcome the challenges found in traditional catalysts.

Antimicrobial peptides (AMPs) are a promising alternative to antibiotics to combat drug resistance in pathogenic bacteria. However, the development of AMPs with high potency and specificity remains a challenge, and new tools to evaluate antimicrobial activity are needed to accelerate the discovery process. As a step toward direct prediction of the experimental minimum inhibitory concentration (MIC) of AMPs, we proposed MBC-Attention, a combination of a multi-branch CNN architecture and attention mechanism. Using a curated dataset of 3929 AMP against Escherichia coli, the optimal MBC-Attention model achieved an average Pearson correlation coefficient of 0.775 and an RMSE of 0.533 (log μM) in three independent tests of 393 sequences each. This results in a 5–12% improvement in PCC and 7–13% improvement in RMSE compared with RF and SVM models. Ablation studies confirmed that both attention mechanisms contributed to performance improvement.

Nowadays, the massive use of tires generates large stocks of waste material which is a serious environmental problem. The usual method used for processing wasted tires is mechanical crushing, in which fiber, steel, and rubber are separated. The aim of this research is the recycling of the obtained rubber, called also GTR (Ground Waste Tires). With this purpose, the paper analyses the mechanical properties of the composites produced by mixing GTR with several industrial polymers. These composites are characterized by the percentage of GTR in the composite and its particle size. These two variables along with seven industrial polymers define a set of composites from which the mechanical properties are analyzed and presented. From the results, it can be drawn that this proposal could be a way to enhance some polymer properties and to contribute in some way to reduce the environmental wasted tires problem.

It was recently demonstrated that a co-planar capacitive sensor could be applied to the evaluation of materials without the disadvantages associated with the other techniques. This technique effectively detects changes in the dielectric properties of the materials due to, for instance, imperfections or variations in the internal structure, by moving a set of simple electrodes on the surface of the specimen. An AC voltage is applied to one or more electrodes and signals are detected by others. This is a promising inspection method for imaging the interior structure of the numerous materials, without the necessity to be in contact with the surface of the sample. In this paper, Finite Element (FE) modelling was employed to simulate the electric field distribution from a co-planar capacitive sensor and the way it interacts with a non-conducting sample. Physical experiments with a prototype capacitive sensor were also performed on a Plexiglas sample with sub-surface defects, to assess the imaging performance of the sensor. A good qualitative agreement was observed between the numerical simulation and experimental result.

The sugar company Valdez S.A. Entity located within the geographical limits of the city of Milagro, needs to reduce its emissions to the environment and does not always comply with the air emissions standards for stationary combustion sources, which indicates that for equipment installed before 2003 they have a maximum limit of 300 mg / m³. A mist eliminator was designed to work inside the original wet gas scrubber of the water-tube cauldron #10, which uses Bagasse as fuel, for the generation of steam for industrial use. The research is documentary and field. The methodology used was mixed. focusing on the comparison of three types of technologies to meet the objectives, the fog eliminators types: Demister, Cyclone and Chevron. To find the appropriate complement, a comparison sheet was made, which is a table of contents evaluated quantitatively, analyzing indicators formulated in each of the contents. The results, supported by the Multiple Criteria Decision Analysis methodology, select the Chevron type fog eliminator, with the best efficiency for capture. Using AutoCAD, allows to visualize in 3D, the structural design in the gas scrubber.

The IEEE 802.15.4-2015 standard includes the SUN (Smart Utility Networks) modulations, i.e., SUN-FSK, SUN-OQPSK and SUN-OFDM, which provide long range communications and allow to trade data rate, occupied bandwidth and reliability. However, given the constraints of low-power devices and the challenges of the wireless channel, communication reliability cannot still meet the PDR (Packet Delivery Ratio) requirements of industrial applications, i.e., PDR>99%. Hence, in this paper we evaluate the benefits of improving communication reliability by combining packet transmissions with modulation diversity using multiple IEEE 802.15.4g SUN modulations. The results derived from a real-world deployment show that going from 1 to 3 packet transmissions with the same SUN modulation can increase PDR from 85.0/84.6/71.3% to 94.2/94.1/86.0% using SUN-FSK, SUN-OQPSK and SUN-OFDM, respectively. Combining the same number of packet transmissions with modulation diversity allows to further increase the average PDR to 97.1%, indicating its potential as a tool to help meeting the reliability requirements of industrial applications.

In this article we present a deployment of 11 nodes using the three different SUN (Smart Utility Network) modulation schemes, as defined in the IEEE 802.15.4-2015 standard. The nodes were deployed in a 110.044 m2 warehouse for 99 days, and the resulting dataset contains a total of 10.710.868 measurements with RSSI (Received Signal Strength Indicator), CCA (Clear Channel Assessment) and PDR (Packet Delivery Ratio) values. The analyzed results show a high variability in average RSSI (i.e., between -82.1 dBm and -101.7 dBm) and CCA (i.e., between -111.2 dBm and -119.9 dBm) values, which are caused by the effects of multi-path propagation and external interference. Despite being above the sensitivity limit for each modulation, this values result in poor average PDR values (i.e., from 65.9% to 87.4%), indicating that additional schemes are required for low-power wireless communications to meet the dependability requirements of industrial applications. For that purpose, we also introduce the concept of modulation diversity, which can be combined with packet repetition to meet such requirements (i.e., PDR>99%) while minimizing the energy expenditure of nodes and meeting regulatory constraints.

Invasion ecology has a long tradition of searching for traits distinguishing alien invasive and non-invasive plants. Surprisingly, this approach has been so far poorly used to understand why some arable weeds are abundant and widespread while others are rare and narrowly distributed. In the present study, we focused on the characteristics of successful weeds occurring in maize fields, one of the most import crop worldwide. Two national weed surveys conducted in France were used to identify increasing and decreasing species based on 175 and 484 surveyed fields in the 1970s and the 2000s, respectively. Weed trait values related to regional frequency, local abundance and specialization to maize were identified with Phylogenetic Generalized Least-Squares (PGLS). We found a positive relationship between regional frequency and local abundance, i.e. the most widespread weeds were also locally more abundant. We highlighted that weeds with the C4 photosynthetic pathway and summer emergence were more abundant, more frequent and more specialized to maize crops. More generally, we highlighted two successful strategies: on the one hand, traits related to a general weediness syndrome with rapid resource acquisition (high SLA and Ellenberg-N) and high colonization capacity (seed longevity, fecundity and wind dispersal), on the other hand, traits related to specific adaptation to spring cultivation (thermophilous species with summer emergence, late flowering and C4 photosynthetic pathway). Deviations from the abundancy-frequency relationships also indicated that species of the Panicoideae sub-family, species with Triazine-resistant populations and neophyte species were more abundant than expected by their regional frequency. To some extent, it is therefore possible to predict which species can be troublesome in maize crops and use this information in weed risk assessment tools to prevent new introductions or favor early detection and eradication. This study showed how tools developed in functional and macro-ecology can be used to improve our understanding of weed ecology and to develop more preventive management strategies.

Barley straw was used to reinforce PHB in a discontinuous semi-industrial process. Four different fibres were used as reinforcing material : sawdust (SW), defibred (DFBF), delignified (DBF) and bleached (BBF) fibres. Looking at the mechanical properties, onlythe elastic moduli (Et) revealed an improvement. Oppositely, the strengths at break, under both tensile and bending assays, tended to decrease, evidencing a poor affinity between both components. Thanks to the mechani-cal treatment applied on the fibre, DFBF appeared as the most promising filler with the mechani-cal properties of the composites closest to those of neat PHB. DFBF-based composites were then produced by means of a process intensification using a twin-screw extruder, and then moulded into flowerpots. Mechanical results showed almost the same properties between the discontinuous and intensification processes. The suitability of the material to be used on agriculture flowerpots was demonstrated by simulation. . PHB-DFBF composite material can be considered an alterna-tive to replace petrol-based products for applications in agriculture and horticulture.

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.

Correlations among estrus cycle, pyometra, and canine diabetes mellitus (CDM) have been described since the late 1950s, and substantial progress in understanding mechanisms beyond was achieved nowadays. Progesterone-related diabetes mellitus (PRDM) in dogs is known for its particular potential for diabetes remission. Thus, a deep understanding of the physiopathological aspects involved is crucial to postulate treatment guidelines to improve the PRDM remission rate, as well as to inform preventive measures. This narrative review aims to provide relevant detailed information on 1) canine estrus cycle and its impact on CDM etiology and management, 2) the role of pyometra as a further cause of insulin resistance, and 3) useful individual therapeutic and preventive strategies. Pharmacological annulment of progesterone effects, as well as inflammatory and progesterone-related conditions resolution in association with adequate exogenous insulin therapy, and residual beta cell function, are key aspects to achieve remission, or at least to improve diabetic clinical control. In this way, spaying should be considered mandatory in most PRDM cases. Preventive measures against CDM can include spaying recommendations; however, individual-based recommendations should be considered since castration may be associated with some long-term health issues.

Affinity chromatography on procainamide-Sepharose has been an important step in the purification of butyrylcholinesterase (BChE) and acetylcholinesterase (AChE) since its introduction in 1978. The procainamide affinity gel has limitations. In the present report a new affinity gel called Hupresin^® was evaluated for its ability to purify truncated, partly-deglycosylated human butyrylcholinesterase (rHuBChE) expressed in a stably transfected CHO cell line. We present a detailed example of the purification of rHuBChE secreted into 3940 mL of serum-free culture medium. The starting material contained 13,163 units of BChE activity (20.9 mg). rHuBChE was purified to homogeneity in a single step by passage over 82 mL of Hupresin^® and elution with 0.1 M tetramethylammonium bromide in 20 mM TrisCl pH 7.5. The fraction with the highest specific activity of 630 units/mg contained 11 mg of BChE. Hupresin^® is superior to procainamide-Sepharose for purification of BChE, but is not suitable for purifying native AChE because Hupresin^® binds AChE so tightly that AChE is desorbed with denaturing solvents such as 50% acetonitrile or 1% trifluoroacetic acid. Procainamide-Sepharose will continue to be useful for purification of AChE.

Clinical rehabilitation and sports performance analysis both require the objectification of movement. Kinovea^© is a free 2D motion analysis software that enables the establishment of kinematics parameters. This low-cost technology has been used in sports sciences, as well as clinical field and research work. Although it has been validated as a tool with which to assess time-related variables, this is not yet the case regarding angular and distance variables. The main objective of this study was to determine the validity and reliability of the Kinovea software in obtaining angular and distance data at different perspectives of 90°, 75°, 60° and 45°. For this purpose, a figure with 29 points was designed (in AutoCAD) and 24 frames analysed. Each frame was examined by three observers who each made two attempts. For each export data item, 20 angles and 20 distance variables were calculated, with intra- and inter-observer reliability also analysed. To evaluate Kinovea reliability and validity a multiple approach was applied involving the following analysis: -systematic error with a two-way ANOVA 2x4; -relative reliability with ICC and CV (95% confidence interval); -absolute reliability with Standard Error. The results thus obtained indicate that the Kinovea software is a valid and reliable tool that is able to measure accurately at distances up to 5 m from the object and at an angle range of 90°–45°. Nevertheless, for optimum results an angle of 90° is suggested.

In this study, we investigated water transparency estimation models in the hypertrophic lagoon of the Albufera of Valencia using Sentinel-2 images. Water transparency, a crucial environmental indicator, was assessed via Secchi disk depth (ZSD) measurements. Three optical models (R490/R560, R490/R705, R560/R705) were explored to establish a robust algorithm for ZSD estimation. Through extensive field sampling and laboratory analyses, weekly data spanning 2018 to 2023 were collected, including water transparency, temperature, conductivity, and chlorophyll-a concentration. Remote sensing imagery from the Sentinel-2 mission was employed, and images were processed using SNAP software. The R560/R705 model, calibrated for turbid lakes, emerged as the most suitable. The algorithm's calibration was validated with high correlation coefficients (R2) in both calibration (0.6149) and validation (0.916) phases, demonstrating the model's accuracy in estimating ZSD. This new algorithm significantly outperformed a previous approach, highlighting the importance of tailoring algorithms to specific water body characteristics. The study contributes to improved water quality assessment and resource management, underscoring the value of remote sensing in environmental research.

In response to the growing inspection demand exerted by process automation in component manufacturing, Non-destructive testing (NDT) continues to explore automated approaches that utilize deep learning algorithms for defect identification, including within digital X-ray radiography images. This necessitates a thorough understanding of the implication of image quality parameters on the performance of these deep learning models. This study investigates the influence of two image quality parameters, namely Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), on the performance of U-net deep learning segmentation model. Input images were acquired with varying combinations of exposure factors such as kilovoltage, milli-ampere, and exposure time, which altered the resultant quality. The data was sorted into 5 different datasets according to their measured SNR and CNR values. The deep learning model was trained 5 distinct times, utilizing a unique dataset for each training session. Training the model with high CNR values yielded an intersection over Union (IoU) metric of 0.9594 on test data of the same category but drops to 0.5875 when tested on lower CNR test data. The result in this study emphasizes the importance of achieving a balance in training dataset according to the investigated quality parameters, to enhance the performance of deep learning segmentation models in NDT radiography applications.

The recent resurgence of yellow fever virus (YFV) activity in the tropical regions of Africa and South America has sparked renewed interest in this infamous arboviral disease. YFV had been a human plague for centuries prior to the identification of its urban transmission vector, the Aedes aegypti mosquito species, and the development of an efficient live-attenuated vaccine, the YF-17D strain. The combination of vector-control measures and vaccination campaigns drastically reduced YFV incidence in humans on many occasions, but the virus never ceased to circulate in the forest, through its sylvatic invertebrate vector(s) and vertebrate host(s). Outbreaks recently reported in Central Africa (2015-2016) and Brazil (since late 2016), reached considerable proportions in terms of spatial distribution and total numbers of cases, with multiple exports, including to China. In turn, questions regarding the likeliness of occurrence of large urban YFV outbreaks in the Americas or of a successful import of YFV to Asia are currently resurfacing. This two-part review describes the current state of knowledge and gaps regarding the molecular biology and transmission dynamics of YFV, along with an overview of the tools that can be used to manage the disease at the individual, local and global levels.

In this paper, we propose and evaluate two mechanisms aimed at improving the communication reliability of IEEE 802.15g SUN (Smart Utility Networks) in industrial scenarios: RTS (Re-Transmission Shaping), which uses acknowledgements to track channel conditions and dynamically adapt the number of re-transmissions per packet, and AMS (Adaptive Modulation Selection), which makes use of reinforcement learning based on MAB (Multi-Armed Bandits) to choose the modulation that provides the best reliability for each packet re-transmission. The evaluation of both mechanisms is performed through computer simulations using a dataset obtained from a real-world deployment and two widely used metrics, the PDR (Packet Delivery Ratio) and the RNP (Required Number of Packet transmissions). The PDR measures the ratio between received and transmitted packets, whereas the RNP is the number of packet repetitions before a successful transmission. The results show that both mechanisms allow to increase the communication reliability while not jeopardizing the battery life-time constraints of end devices. For example, when three re-transmissions per packet are allowed, the PDR reaches 98/96\% with a RNP of 2.03/1.32 using RTS and AMS, respectively. Additionally, the combination of both proposed mechanisms allows to reach a 99% PDR with a RNP of 1.7, making IEEE 802.15.4g SUN compliant with the stringent data delivery requirements of industrial applications.

Curcumin, found in the rhizome of turmeric, has extensive therapeutic promises via its antioxidant, anti-inflammatory, and antiproliferative properties. Preclinical in vitro and in vivo data have shown curcumin to be an effective treatment for multiple cancers. These effects are drived by curcumin's ability to induce G2/M cell cycle arrest, induction of autophagy, activation of apoptotic pathways, disruption of molecular signaling, inhibition of invasion and metastasis, and by increasing the efficacy of existing chemotherapeutics. Here we focused on the hormetic behaviour of curcumin. Frequently, low doses of toxins and other stressors not only are harmless but also activate an adaptive stress whereas high dose activates acute responses like autophagy and cell death. This phenomenon is referred to as hormesis. Many molecules that cause cell death elicite an initial autophagic step that is a cytoprotective mechanism relying on elimination of dysfunctional structures intracellular, notably by mitophagy. This phenomenon is considered as a primarily protective mechanism against stressors. At higher doses, cells undergo mitochondrial outer membrane permeabilization due to calcium release from the endoplasmic reticulum and die. Herein, we address the complex crosstalk between the induced mitochondrial biogenesis, mitochondrial destabilization accompanied by mitophagy and cell death that can also be at play.

Vaccine refusal and hesitancy pose a critical challenge to public health, leading to delays in vaccination and compromising herd immunity. To address this issue, we conducted a comprehensive observational study on the adult Spanish population in 2021. Through an online questionnaire, we explored the sociodemographic and sociocultural factors, beliefs, and opinions of those refusing or holding hesitancy about vaccines, and their vaccination behaviours by vaccine type and sex. Our findings revealed that vaccine refusal rates were relatively low (16.8%), and mainly associated with influenza vaccination (10.3%). Greater refusal of vaccination was observed in over 60 years old, in those expressing hesitancy due to vaccine components and opposing free and compulsory vaccination, unaware that vaccination protects the community and being against consuming cow’s milk and the use of infant formulas for breastfeeding. Vaccine hesitancy was greatest in individuals under 31 years old, women, parents of children under 15 years old, against compulsory vaccination, unaware that vaccination protects the community, with hesitancy due to vaccine costs, and in favour of alternative and complementary treatments. These insights underscore the need for strategies to improve education about vaccination and dispel misconceptions are crucial for effectively reducing vaccine refusal and hesitancy across the population.

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

A printed Vivaldi antenna that is optically transparent, ultra-wideband (UWB), and reconfigurable has been developed, fabricated, and tested at millimeter wave frequencies. It covers a broad frequency range of 20-30 GHz by using three PIN diodes. The diodes control the current flow to direct the beam of the antenna. The results of numerical simulations and measurements match at millimeter wave frequencies. The design of this antenna is unique as it allows for a reduction in size and ease of integration while also providing the ability to change the radiation pattern by up to 300 degrees, making it suitable for 5G and 6G communications. Additionally, this antenna can also be useful for RF applications that require dynamic switching of radiation patterns and cognitive radio.

In this article, it is proposed to use aluminum breakage scraps to obtain Green Hydrogen through the aluminum-water reaction with caustic soda as a catalyst. From this exothermic reaction, both hydrogen and the heat generated can be used. Due to the low price of aluminum chips, this allows us to produce Green hydrogen below the current price that is obtained using renewable energy sources and electrolyzers. On the other hand, we have developed a process that is sustainable since it is obtained as alumina and caustic soda waste that can be reused. This alumina obtained, once filtered, has high purity which allows us to produce high-quality primary aluminum without the need to use bauxite and reducing the production of red sludge. A comparative study-analysis has been carried out of two of the types of forms in which the most common aluminum is presented in the industry to analyze which one performs better by studying key factors such as the hydrogen produced, and the waste generated during the process. Finally, the mathematical model has been defined to be able to control the flow based on different key parameters such as temperature, molarity, and geometry. Undoubtedly, the study that we present represents a milestone for the recovery of metallic aluminum waste and may be of great interest to industries that use aluminum in their processes, such as recuperators, but also the vehicle or aerospace industry.

In this paper, ground tire rubber (GTR) was mechano-chemically modified with road bitumen 160/220 and subsequently treated using a microwave radiation. The combined impact of bitumen 160/220 content and microwave treatment on short-term devulcanization of GTR were studied by thermal camera, wavelength dispersive X-ray fluorescence spectrometry (WD-XRF), static headspace and gas chromatography-mass spectrometry (SHS-GC-MS), thermogravimetric analysis combined with Fourier transform infrared spectroscopy (TGA-FTIR), oscillating disc rheometer and static mechanical properties measurements. The obtained results showed that bitumen plasticizer prevent oxidation of GTR during microwave treatment and simultaneously improves processing and thermal stability of obtained reclaimed rubber.

Several studies have shown that changes in incoming solar radiation and variations of the diffuse fraction can significantly modify the vegetation carbon uptake. Hence, monitoring the incoming solar radiation at large scale and with high temporal frequency is crucial for this reason along with many others. The EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA SAF) operationally disseminates in near real time estimates of the downwelling shortwave radiation at the surface since 2005. This product is derived from observations provided by the SEVIRI instrument onboard the Meteosat Second Generation series of geostationary satellites, which covers Europe, Africa, the Middle East, and part of South America. However, near real time generation of the diffuse fraction at the surface level has only recently been initiated. The main difficulty towards achieving this goal was the general lack of accurate information on the aerosol particles in the atmosphere. This limitation is nowadays less important thanks to the improvements in atmospheric numerical models. This study presents an upgrade of the LSA-SAF operational retrieval method, which provides the simultaneous estimation of the incoming solar radiation and its diffuse fraction from satellite every 15 minutes. The upgrade includes a comprehensive representation of the influence of aerosols based on physical approximations of the radiative transfer within an atmosphere-surface associated medium. This article explains the retrieval method, discusses its limitations and differences with the previous method, and details the characteristics of the output products. A companion article will focus on the evaluation of the products against independent measurements of solar radiation. Finally, the access to the source code is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable.

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

This work explored and contrasted the effect of microstructure on the tensile properties of AlSi10Mg alloys generated by transient directional solidification depending on variations in cooling rate and Magnesium (Mg) content (i.e., 0.45 and 1wt.% Mg), with a focus on understanding the dendritic growth and phases constitution. Optical and Scanning electron (SEM) microscopies, CALPHAD and thermal analysis were used to describe the microstructure, forming phases and resulting tensile properties. The findings showed that the experimental evolution of the primary dendritic spacing is very similar when both directionally solidified (DS) Al-10wt.% Si-0.45wt.% Mg and Al-10wt.% Si-1wt.% Mg alloys samples are compared. The secondary dendritic spacing was lower for the alloy with more Mg, especially considering the range of high growth velocities. Moreover, a greater fraction of (Al+Si+Mg2Si) ternary eutectic islands surrounding the -Al dendritic matrix was noted for the alloy with 1wt.% Mg. As a result of primary dendritic spacings greater than 180 m related to lower cooling rates, slightly higher tensile properties were attained for the Al-10wt.% Si-0.45wt.% Mg alloy. In contrast, combining dendritic refining (< 150 m) and larger Mg2Si fraction, fast solidified DS Al-10wt.% Si-1wt.% Mg samples exhibited higher tensile strength and elongation. The control of cooling rate and fineness of the dendritic array provided a new insight related to the addition of Mg in slightly higher levels than conventional ones, capable of achieving a better balance of tensile properties in AlSi10Mg alloys.

High frequency knowledge of the spatio-temporal distribution of the Downwelling Surface Shortwave Flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface-atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The EUMETSAT Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (Downwelling Surface Short-wave radiation Fluxes – Total and Diffuse fraction) product with an operational status since the year 2019. The method for the retrieval was presented in the companion paper [40]. The part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents the comparison of the corresponding outputs, i.e. total DSSF and diffuse fraction (fd) components, against in-situ measurements acquired at four BSRN stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20Wm^-2 for DSSF<200Wm^-2, and 10% for DSSF>=200Wm^-2. The MBE and rMBE compared to the ground measurements are 3.618Wm^-2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd<0.5, and 20% for fd>=0.5. The MBE and rMBE compared to the ground measurements are -0.044 and -17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud-aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the Aerosol Optical Depth (AOD) forecasts currently available is enough accurate to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.

This review explores the transformative role of induced pluripotent stem cells (iPSCs) and organoids in advancing neuropathology research. Focused on Alzheimer's disease, epilepsy, Parkinson's disease, and spinal cord injury, iPSCs offer patient-specific disease modeling with regenerative therapy potential. The versatility of iPSCs, their ability to differentiate into the main neuronal cell types, and their integration into three-dimensional organoid models enable the recreation of complex tissues in vitro. Improvement of organoid and iPSCs generation protocols and the selection of appropriate donor cell types are highlighted as crucial steps toward the application of these new technologies to overcome tumorigenic potential and other challenges. iPSCs demonstrate promise in regenerative therapies, as evidenced by successful applications in animal models.

Trait anxiety, emotion regulation strategies, and metacognitive beliefs influence executive functions (EF) and academic achievement. This study examines their interplay and impact on academic success. In total, 275 adolescents (10-17 years) and parents completed an online questionnaire assessing trait anxiety, emotion regulation strategies, metacognition, parent-reported behaviors related to executive functioning, and overall school average. Preliminary analyses confirmed consistency with existing literature for each variable and their interaction. Furthermore, we conducted a network analysis among the main variables. This analysis supports the need to pay more attention to reflective variables - maladaptive emotion regulation strategies and metacognitive beliefs about worry - when studying trait anxiety. These variables were linked to problematic executive functioning in adolescents. These latter had a negative link to academic achievement. This study offers innovative insights by investigating less-explored relationships in the scientific literature. It reveals high and significant correlations between metacognitive beliefs, maladaptive emotion regulation strategies and trait anxiety (r &gt; .500, p &lt; .001) but also between these variables and both executive functioning and academic achievement. These findings offer new perspectives for research and underscore the importance of holistically examining psychological factors related to academic success.

Age-related macular degeneration (AMD) is a common ocular disease characterized by the de-generation of the central area of the retina in elderly population. Progression and response to treatment is influenced by genetic and non-genetic factors. Proteomics is a powerful tool to study, at the molecular level, the mechanisms underlaying the progression of the diseases, to identify new therapeutical targets and to establish biomarkers to monitor progression and treatment ef-fectiveness. In this work we pursue to systematically review the use of proteomic-based ap-proaches for the study of the molecular mechanisms underlying the development of AMD, as well as the progression of the disease and the on-treatment patient monitoring. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines were followed. Proteomic approaches have identified key players on the onset of the disease, such as proteins involved in lipid metabolism and oxidative stress, but also in the progression to advanced stages, including factors related to extracellular matrix integrity and angiogenesis. Although an-ti-vascular endothelial growth factor (anti-VEGF)-based therapy has been crucial in the treatment of neovascular AMD it is necessary to get deeper into the underlying disease mechanisms to move forward to next-generation therapies of the later-stage forms of this multifactorial disease.

Many engineering systems are described by using differential models whose solutions, generally obtained after discretization, can exhibit a noticeable deviation with respect to the response of the physical systems that those models are expected to represent. In those circumstances one possibility consists of enriching the model in order to reproduce the physical system behavior. The present paper considers a dynamical system, and proposes enriching the model solution by learning the dynamical model of the gap between the system response and the model-based prediction, while ensuring that the time integration of the learnt model remains stable. The proposed methodology is applied on the simulation of the top-oil temperature evolution of a power transformer, whose data is provided by RTE, the French Electricity Transmission System Operator.

Mandibular third molar is the most frequently impacted tooth. Mandibular third molar impaction bears consequences on the adjacent mandibular second molar (MSM) like bone loss. It can be identified initially using orthopantomography (OPG). The objective is to compare the changes in the bone level distal to MSM between patients with extracted and non-extracted impacted man-dibular third molars (IMTM) using OPG. In this retrospective case-control study, 160 archived (OPGs) of 80 patients visiting the Dental Hospital of the University of Barcelona (HOUB) were randomly selected. The participants were stratified into two groups. The study group involved measuring the bone level distal to the mandibular second molar before and after the extraction of the IMTM. The control group, on the other hand, had bone levels measured twice within 3–6-month period without the extraction of the IMTM. The mean ages of patients in study and control groups were 35.5 ± 15.45 and 33 ± 16.49, respectively. Study group demonstrated signifi-cant (p < 0.05) bone gain after extraction, whereas control group demonstrated significant bone loss (p < 0.0001) after follow-up. Bone improvements were observed distal to the mandibular second molar after the extraction of the IMTM compared to those in control group.

First described in 1760 by the anatomist Morgagni, CoA is a congenital heart defect characterized by narrowing the aorta, typically distal to the left subclavian artery. It accounts for approximately 5-8% of all congenital heart diseases, with an incidence estimated at 4 per 10,000 live births. In 1944, the Swedish surgeon Clarence Crafoord achieved the first successful surgical CoA repair by performing an aortic end-to-end anastomosis on two patients aged 12 and 27 years old. Presently, the most prevalent techniques for surgical repair, particularly in infants and neonates with isolated coarctation, involve resection with end-to-end anastomosis (EEA) and the modified Crafoord technique (extended resection with end-to-end anastomosis (EEEA)). Subclavian flap aortoplasty (SCAP) is an alternative surgical option for CoA repair in patients under two years of age. In cases where the stenosis extends beyond resection and end-to-end anastomosis feasibility, patch aortoplasty (PP) employing a prosthetic patch can augment the stenotic region, especially for older patients. Despite advances in pediatric cardiology and cardiac surgery, recoarctation remains a significant concern after surgical or interventional repair. This comprehensive review aims to provide a thorough analysis of coarctation management, covering the pioneering techniques introduced by Crafoord using head-to-tail anastomosis and now extending to the contemporary era marked by percutaneous interventions as well as the recoarctation rate associated with each type.

Atrophy quantification is fundamental for understanding brain development and diagnosing and monitoring brain diseases. FSL-SIENA is a well-known fully-automated method that has been widely used in brain magnetic resonance imaging studies. However, intensity variations arising during image acquisition that may compromise evaluation, analysis and even diagnosis. In this work, we study whether intensity standardisation can improve longitudinal atrophy quantification. We considered seven methods comprising z-score, fuzzy c-means, Gaussian mixture model, kernel density, histogram matching, white stripe, and removal of artificial voxel effects by linear regression (RAVEL). We used a total of 330 scans from two publicly-available datasets, ADNI and OASIS. In scan-rescan assessments, that measures robustness to subtle imaging variations, intensity standardisation did not compromise the robustness of FSL-SIENA significantly (p>0.1). In power analysis assessments, that measures the ability to discern between two groups of subjects, three methods led to consistent improvements in both datasets with respect to the original: fuzzy c-means, Gaussian mixture model, and kernel density estimation. Reduction in sample size using these three methods ranged from 17% to 95%. The performance of the other four methods was affected by spatial normalisation, skull stripping errors, presence of periventricular white matter hyperintensities, or tissue proportion variations over time. Our work evinces the relevance of appropriate intensity standardisation in longitudinal cerebral atrophy assessments using FSL-SIENA.

Packet re-transmissions are a common technique to improve link reliability in low-power wireless networks. However, since packet re-transmissions increase the end-device energy consumption and the network load, a maximum number of re-transmissions per packet is typically set, also considering the duty-cycle limitations imposed by radio-frequency regulations. Moreover, the number of re-transmissions per packet is typically set to a constant value, meaning that all packet re-transmissions are treated the same regardless of actual channel conditions (i.e., multi-path propagation or internal/external interference effects). Taking that into account, in this paper we propose and evaluate the concept of re-transmission shaping, a mechanism that manages packet re-transmissions to maximize link reliability, while minimizing energy consumption and meeting radio-frequency regulation constraints. The proposed re-transmission shaping mechanism operates by keeping track of unused packet re-transmissions and allocating additional retransmission when the instantaneous link quality decreases due to channel impairments. To evaluate the re-transmission shaping mechanism we use trace-based simulations using a IEEE 802.15.4g SUN data-set and two widely used metrics, the PDR (Packet Delivery Ratio) and the RNP (Required Number of Packets). The obtained results show that re-transmission shaping is a useful mechanism to improve link reliability of low-power wireless communications, as it can increase PDR from 77.9% to 99.2% while sustaining a RNP of 2.35 re-transmissions per packet, when compared to using a single re-transmission per packet.

Recent research has revealed surprisingly important connections between animals’ microbiome and social behaviour. Social interactions can affect the composition and function of the microbiome; conversely, the microbiome affects social communication by influencing the hosts’ central nervous system and peripheral chemical communication. These discoveries set the stage for novel research venues focusing on the evolution and physiology of animal social behaviour in relation to microbial transmission strategies. Here, we discuss the emerging roles of teleost fish model candidates and their key potential for advancing research fields linked to sociality and microbial regulation. We argue that fish models, such as the zebrafish, sticklebacks, guppies and cleaner-client dyads, will provide valuable insights into the roles of microbiome in shaping social behaviour and vice versa, while also being of direct relevance to the food and ornamental fish trades.

This study is framed on the Information Theory as a constructive criterion to generate probabilistic distributions –through the elaboration of Bayesian Networks- and to reduce the uncertainty in the occurrence and relationship between two key psychological variables associated with the sports’ performance: Self-Determined Motivation and Competitive Anxiety. We analyzed 674 universitary students/athletes who competed in the 2017 Universitary Games (Universiade) in México, from 44 universities, with an average age of 21 years old (SD = 2.07), and with a sportive experience of 8.61 years of average (SD = 5.15). Methods: Regarding the data analysis, first of all a CHAID algorithm was carried out for to know the independence links among variables, and then two Bayesian networks (BN) were elaborated. The validation of the BN revealed AUC values ranging from 0.5 to 0.92. Subsequently, various instantations were carried out with hypothetical values applied to the “bottom” variables. Results showed two probability trees that have Extrinisic Motivation and Amotivation at the top, while the anxiety/activation due to the worry for performance was at the bottom of probabilities. The instantiations carried out support the existence of these probabilistic relationships, demonstrating the little influence on the competition anxiety generated by the intrinsic motivation. In conclusion, the reduction of the uncertainty made up by the restricted BN may aloe to re-introduce Information Theory principles in psychosocial studies, allowing authors to obtain useful probabilities values upon target psychological variables related with sportive performance.

The early failure of glaucoma surgery is mainly caused by an overly fibrosis at the subconjunctival space causing obliteration of the filtration bleb. Because fibrosis has a suspected basis of genetic predisposition, we have undertaken a prospective study to identify upregulated profibrotic genes in a population of glaucoma patients with signs of conjunctival fibrosis and early postoperative surgical failure. Clinical data of re-operated fibrosis patients, hyperfibrosis patients re-operated more than once in a short time, and control patients with no fibrosis were recorded and analyzed at each follow-up visit. Conjunctival-Tenon surgical specimens were obtained intraoperatively to evaluate the local expression of a panel of genes potentially associated with fibrosis. In order to correlate gene expression signature with protein levels, we quantified secreted proteins in primary cultures of fibroblasts from patients. Expression of VEGF-A, IL-8, C-MYC, and CDKN1A was induced in the conjunctiva of hyperfibrosis patients. VEGF-A and IL-8 protein levels were also increased in fibroblast supernatants. We propose that these proteins may act as biomarkers of conjunctival fibrosis in glaucoma patients undergoing filtering surgery. Molecular markers could be crucial for early detection of patients at high risk of failure of filtration surgery leading to more optimal and personalized treatments.

Iron is the most abundant micronutrient in plant mitochondria and it has a crucial role in biochemical reactions involving electron transfer. It has been described in Oryza sativa that Mitochondrial Iron Transporter (MIT) is an essential gene and that knockdown mutant rice plants have a decreased amount of iron in mitochondria, strongly suggesting that OsMIT is involved in mitochondrial iron uptake. In Arabidopsis thaliana, two genes encode MIT homologues. In this study, we analyzed different AtMIT1 and AtMIT2 mutant alleles, confirming that individually AtMIT1 nor AtMIT2 genes are essential. When we generated crosses between Atmit1 and Atmit2 alleles we were able to isolate homozygous double mutant plants. Interestingly, homozygous double mutant plants were obtained only when mutant alleles of Atmit2 with the T-DNA insertion in the intron region were used for crossings, and in these cases a correctly spliced AtMIT2 mRNA was generated, although at a low level. Atmit1 Atmit2 double homozygous mutant plants, which were knockout for AtMIT1 and knockdown for AtMIT2, were grown and chacterised in iron sufficient conditions. Pleiotropic developmental defects were observed including abnormal seeds, increased number of cotyledons, slow growth rate, pinoid stems, defects in flower structures and reduced seed set. We observed a possible phenomenon of T-DNA suppression in the next generation of Atmit1 Atmit2 double homozygous mutant plants, correlating with an increased splicing of the AtMIT2 intron containing the T-DNA. Molecular analysis of gene expression markers for mitochondrial and oxidative stress showed that Atmit1 Atmit2 double homozygous mutant plants express a degree of mitochondrial perturbation. A RNA-Seq study was performed and we could identify more than 760 genes differentially expressed in Atmit1 Atmit2, including genes involved in iron transport, coumarin metabolism, and hormones metabolism, transport and signaling. Our data suggest that some of the phenotypes observed in Atmit1 Atmit2 double homozygous mutant plants are mediated by defects in auxin homeostasis.