Antimicrobial resistance (AMR) poses a critical global health threat, leading to approximately 1.27 million deaths annually from infectious diseases resistant to existing antibiotics. Factors such as antibiotic misuse and environmental contamination have accelerated AMR, with the COVID-19 pandemic exacerbating the issue due to increased antibiotic usage. However, the development of new antibiotics has stagnated, with only a few approved in recent years, and many facing resistance. Among the priority pathogens identified by the WHO, Pseudomonas aeruginosa stands out as a significant concern due to its multidrug resistance and virulence. P. aeruginosa infections are challenging to treat due to intrinsic and acquired resistance mechanisms, as well as its ability to form biofilms. Additionally, P. aeruginosa produces a plethora of virulence factors, including proteases, siderophores, and toxins, further complicating treatment. Quorum sensing (QS) systems play a crucial role in regulating bacterial physiology and virulence factor expression. P. aeruginosa employs three QS systems, making it an attractive target for quorum quenching (QQ) strategies. Enzymes such as AHL lactonases, acylases, and oxidoreductases have shown promise in inhibiting QS, thus reducing virulence without impacting bacterial growth. Furthermore, natural QS inhibitors produced by various organisms offer potential therapeutic alternatives. Despite promising results in vitro, translating QQ strategies to clinical settings remains challenging. Nevertheless, QQ represents a novel approach in combating multidrug-resistant infections and warrants further investigation as a complementary therapeutic strategy alongside traditional antibiotics. This review summarizes enzymes with Qurorum Quenching activity evaluated against the pathogen P. aeruginosa and their potential applications in combination therapies.

Clinical evidence has shown that bacterial infections are more difficult to eradicate when form-ing a biofilm aggregate than when are produced by bacteria in planktonic form. Therefore, com-pounds that inhibit biofilm formation could be used against severe infections. It has been re-ported that bromo 2-(5H) furanones inhibited biofilm formation by their anti-quorum sensing properties. To determine if the 2-(5H) furanone moiety is essential to induce inhibition of biofilm formation, we evaluated ten halogen 2-(5H) furanones derivates previously synthesized. Besides evaluating the inhibition of biofilm formation, we assessed pyocyanin production, swarming motility, and transcription of essential QS genes: rsaL, rhlA, pqsA and phz1 genes. Our results showed that although three bromo-furan-2(5H)-one-type derivatives (A1-A3) and two bromo-4-(phenylamino)-furan-2(5H)-one-type compounds (B2 and B6) inhibited the biofilm formation in both P. aeruginosa PA14 (reference) and PA64 (drug-resistant) strains only the furanones A1-A3 were efficient to inhibit QSS.

Zidovudine (AZT) has significantly reduced the mortality and morbidity rates among AIDS patients, but it has been associated with hepatotoxicity. AZT treatment has been linked to disrupted lipid and glucose metabolism, and the enhancement of pro-inflammatory chemokines and other mediators, which can lead to liver steatosis. In contrast, the administration of adenosine (ADO) has proven to be an effective hepatoprotector against both acute and chronic liver damage. Therefore, present study was aimed to investigate the harmful effects of chronic AZT administration and the beneficial effects of the co-administered ADO. Chronic oral AZT administration did not induce hyperglycemia or dyslipidemia, but serum liver marker enzyme activities were increased, as well as evidence of liver steatosis and inflammation. These findings were associated with low insulin and glucagon levels, elevated serum levels of pro-inflammatory cytokines and disruptions in cell redox states in these animals. ADO co-administration attenuated the deleterious effects induced by AZT: blocking the production of inflammatory molecules, increasing serum insulin and glucagon levels, and restoring liver cellular redox state. Then, blood insulin levels seemed to be greatly influenced by the cellular redox state, which was altered by AZT administration. This alteration is likely to be connected to mitochondrial integrity and metabolism.

Available options to combat bacterial infections are getting scarce. We require innovative and imaginative approaches to enhance the identification and discovery of effective antimicrobials capable of combating bacteria resistant to multiple or all available drugs. These methods should either directly eliminate the resistant bacteria or influence their viability indirectly by inhibiting their virulence or reducing their resistance to antibacterial agents. One interesting approach is to analyze ancient remedies presumably used to treat bacterial infections, try formulating them, and test them against modern microbes. The field was recently named ancientbiotics. This approach allows us to take advantage of centuries of accumulated empirical knowledge, from several traditional medicines of various ancient cultures across the world. The strategy has already resulted in promising formulations to combat the ESKAPE group of nosocomial pathogens. Moreover, molecular de-extinction consists of genome analysis of extinct species in the search for useful antimicrobials, such as peptides. The de-extinction of simple organisms such as bacteriophages may eventually become a resource for novel tools to combat multidrug-resistant bacteria. In this review, we summarize and discuss the reported antimicrobial effects of ancient remedies and de-extinct molecules known to modern science, and discuss possible new strategies to further harness the potential of past remedies and molecules to help us fight the rise of superbugs.

Industry 4.0 is having a great impact in all smart efforts. This is not a single product, but is composed of several technologies, being one of them Industrial Internet of Things (IIoT). Currently, there are very varied implementation options offered by several companies, and this imposes a new challenge to companies that want to implement IoT in their processes. This challenge suggests to use multi-criteria analysis to make a repeatable and justified decision, requiring a set of alternatives and criteria. This paper proposes a new methodology and comprehensive criteria to help organizations to take an educated decision by applying multi-criteria analysis. Here, we suggest a new original use of PROMETHEE-II with full example from weight calculation up to IoT platform selection, showing this methodology as an effective study for other organizations interested to select an IoT platform. The criteria proposed outstands from previous work by including not only technical aspects, but economic and social criteria, providing a full view of the problem analyzed. A case of study was used to prove this proposed methodology.

We assume that poetic devices have an implicit goal: producing an overall sound scheme that will induce the reader to associate intended and expressed meaning to the sound of the poem. Sounds may be organized into categories and assigned presumed meaning as suggested by traditional literary studies. In my work, I have extracted automatically the sound grids of all the sonnets by William Shakespeare and have combined them with the themes expressed by their contents. In a first experiment I have computed lexically and semantically based sentiment analysis obtaining an 80% of agreement. In a second experiment sentiment analysis has been substituted by Appraisal Theory thus obtaining a more fine-grained interpretation which in some cases contradicts the first one. The computation for the second poet - regarded by many critics the best of last century - includes both vowels and consonants. In addition, it combines automatic semantically and lexically based sentiment analysis with sound grids. The results produce visual maps that clearly separate poems into three clusters: negative harmony, positive harmony and disharmony where the latter instantiates the need by the poet to encompass the opposites in a desperate attempt to reconcile them.

Abstract: This work is part of the interest of solving the problems of water contamination with last generation pollutants, for which a novel and in an aqueous medium FeBTC material incorporated with magnetite nanoparticles was proposed. That material was synthesized by in situ solvothermal method, the Fe3O4 nanoparticles were added during the Fe-BTC MOF synthesis and used in the drug’s adsorption. The materials were characterized by XRD, FTIR and Raman spectroscopy, and N2-physisorption at 77 K. Fe3O4-FeBTC material showed a maximum adsorption capacity of 357.1 mg g−1 for diclofenac sodium, 70.9 mg g−1 for naproxen sodium, and 122.9 mg g−1 for Ibuprofen. A pseudo-second-order kinetic model can describe the adsorption process, and the thermodynamic study revealed that the adsorption of the three drugs was a feasible, spontaneous, and exothermic process. The incorporation of magnetite nanoparticles in the FeBTC considerably increased the adsorption capacity of pristine FeBTC. Also, hybridization of the FeBTC with magnetite nanoparticles reinforced the most vulnerable part of the MOF, increasing its thermal and aqueous media stability. The electrostatic interaction, H-bonding, and interactions in the open-metal sites played a vital role in drug adsorption. The competition of sites in the multicomponent mixture's adsorption showed selective adsorption at diclofenac sodium and naproxen sodium.

Computer vision is considered as an ally to solve business problems that require human intervention, intelligence and criteria. This topic of research has evolved in XXI century at faster peace, delivering various alternatives from open source until commercial platforms. With so many options and market growing, it result difficult to make a decision on which one to use, or even worse, realize it was not suited for different scenarios. In this paper we analyze five options selected arbitrarily and tested on a dataset of 755 images to detect persons in an image, using object detectors. We analyze elapsed time to process an image, error with observations by humans, number of persons detected, correlation of time and person density, object detected size and F1 Score, considering precision and recall. As we found there are score ties and similar behaviors among options available, we introduce a novel index that takes in consideration the number of persons and their pixel size, to propose the Vision Acuity Index of Computer Vision. The results demonstrate this is a good option to serve as indicator to make decisions. Also, this index proposed have a potential to be expanded for different business use cases, and to measure new proposed algorithms in the future along with the traditional metrics used previously.

Background: Boronic acids form di-ester bonds with cis-hydroxyl groups in carbohydrates. The formation of these adducts could impair the physical and chemical properties of the precursors, even their biological activity. Methods: Two carbohydrate-derivatives from D-fructose and D-arabinose and phenylboronic acid were synthesized in a straightforward one-step procedure and chemically characterized by spectroscopy and X-ray diffraction crystallography. Also, an acute toxicity test was performed to determine their Lethal Dose50 (LD50) by using the Lorke’s method. Results: Analytical chemistry assays confirmed adducts by the generation of the diester bonds with a β-D-pyranose of carbohydrates, including signals corresponding to the formation of new bonds, like the stretching of B-O bonds. The NMR spectra yielded information about the stereoselectivity in the synthesis reaction by the finding of just one signal in the range for the anomeric carbon in the 13C NMR spectra of both adducts. The acute toxicity tests showed that LD50 value for both compounds is 1265 mg/kg, while Effective Dose 50 for sedation is 531 mg/kg. However, differences were in the onset and lapse of sedation. Conclusions: These adducts are bioactive and highly safe agents. Further biological evaluation is desirable to explore medical purposes.

In the vaginal ecosystem there is a symbiotic relationship between the microbiota and the host, particularly Candida spp., which are considered commensals of the vaginal mucosa. During pregnancy there is an increase in hormonal secretion that alters the vaginal microbiota and favors the development of Candida infection. Several studies have shown the increased prevalence of Candida during pregnancy, as well as its association with perinatal complications and current clinical practice guidelines recommend fluconazole as the treatment of choice during pregnancy in case of infection by Candida albicans and non-albicans Candida. However, in the Mexican population, this association has not been studied. So in this study, an intentional search for colonization by Candida spp. in pregnant women who attended the obstetric triage of the Hospital Regional de Alta Especialidad de Ixtapaluca during the period from May to October 2019, and they were followed up until the end of the pregnancy. Data on age, number of pregnancies, gestational age, body mass index, and perinatal outcomes were analyzed. Of 83 patients included in the study, yeasts corre-sponding to C. albicans (12) and C. glabrata (4) were isolated in 16. In the group of patients with Candida, the maternal age range was from 15 to 36 years old, of which 7 were adolescents and 2 with advanced maternal age, with an average of 2 gestations, the range of body mass index was from 19.3 to 42.4, of which 4 were overweight and 7 obese. Perinatal complications were observed in three patients, one presented chorioamnionitis and in two the neonates were small for gestational age. No association was found between colonization by Candida spp. and the number of preg-nancies, gestational age, body mass index or perinatal results. However, it was found that age (adolescence) may be a risk factor for the development of vulvovaginitis during pregnancy.

Power Electronic development determines introduction of nonlinear devices in Electric Power Systems. Introduction of nonlinear devices increase current harmonics in Transmission and Distribution Power Systems. Distribution transformers and feeders increase power losses and their nominal parameters are reduced. Present work introduces a procedure to evaluate maximum permissible load in single phase distribution transformers with massive introduction of a new type of nonlinear load which changes daily demand graphs.

This work proposes a physics-based identification technique based on genetic algorithms. The main objective is to obtain a parametric matrix A that describes the time-invariant linear model of the longitudinal dynamics of an aircraft. This is achieved by proposing a fitness function based on the properties of the transition matrix and taking advantage of some of the capabilities of the genetic algorithm, mainly those of restricting the search ranges of the unknowns. In this case, such unknowns are related to the type of aircraft and flight conditions that are considered during the identification process. The proposed identification method is validated with a reliable nonlinear model that can be found in the literature, as well as with the calculation of the trim condition and linearization generally used in aircraft dynamics. In summary, this study suggests the genetic algorithm provided with the adequate fitness function, could be an appealing alternative for aircraft model identification, even when only a limited amount of data is available. Furthermore, in some cases, linearization using genetic algorithm can be more efficient than classical methods.

While some researchers have suggested that the self-employment (SE) sector is a haven during a financial Crisis, others believe that SE is not necessarily the desired outcome, but an indicator that the labor market is tightening for some groups. Few researchers have compared the SE sector before and after the occurrence of a significant financial Crisis, especially in developed countries. This paper analyzes the determinants of entry into self-employment during the 2008 Spanish Crisis. Using data from the Encuesta de Presupuesto Familiar (EPF), results show that although the rate of SE did not experience a significant change during this time the Crisis affected people differently based on gender, with being females more affected than males. Results also suggest differences between Comunidades Autonomas in how the self-employment sector behaved during the Crisis.

This article addresses the emergence of a niche for sustainable agricultural production in the province of García Rovira, Colombia. It examines the intervention of the Colombian planning regime, which implements agendas for sustainable territorial development. However, these agendas are not adequately aligned with provincial realities, resulting in a productive decline. From a multi-level perspective, a niche of production linked to the landscape is identified, highlighting sustainable practices and innovation. The study seeks to understand how planning influences the emergence of such niches and what factors boost their transition to sustainability. Through a mixed methodology, growing sectors are highlighted, and the profiles of the producers involved are outlined. The main conclusion is that the planned intervention is inefficient, as the niche of sustainable production emerges without its clear influence. Therefore, it is proposed to re-evaluate planning using alternative analysis frameworks to detect emerging productive dynamics, serving as a basis for future plans.

Microalgal harvesting is one of the most challenging processes in the development of algal research and development. Several methods, such as centrifugation, flocculation, and filtration, are available at the laboratory scale. However, the requirement of expensive pieces of equipment and the possibility of biomass contamination are recurring gaps that hinder the development of microalgae I+D in different parts of the world. Recently, the electroflotation has been proved as a suitable method for the harvesting of different species of microalgae and cyanobacteria. To this day, there are no companies that sell laboratory-scale electroflotation equipment; this is mainly due to the gap in the knowledge on which factors (time, mixing rate, number of electrodes, and others) will affect the efficiency of concentration without reducing the biomass quality. This paper aims to build an innovative low-cost electroflotation system under 300 USD with cheap and resistant materials. To achieve our goal, we test the interaction of three variables (time, mixing rate, and amount of electrodes) were evaluated. Results showed that an efficiency closer to 100% could be achieved under 20 minutes using >10 electrodes and 150 rpm. We hope this innovative approach can be used by different researchers to improve our knowledge of the concentration and harvesting of algae and cyanobacteria.

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

This study investigates distillery wastewater, commonly known as vinasse, as a potential culture medium for the production of Chlorella vulgaris and its most relevant metabolites. The effect of vinasse concentration on the composition of the biomass (proteins, carbohydrates and lipids) was evaluated in treatments performed in 6-L tubular air-lift reactors. The reactors were operated at 25 °C for 18 days, in total darkness, under a continuous flow of air. Results showed a rapid growth of microalgae in the first ten days, when an average production of 0.87 g/L was reached. Then, the daily biomass productivity began to decrease, up to an average value of 11.8 g/L at the 16th day. For all treatments, there was a significant reduction in the concentration of most metabolites in the first eight days. This was likely due to the adaptation of the biomass to the new conditions, with a transition from autotrophic to heterotrophic metabolism. From the 10th day, the concentration of metabolites in the biomass began to increase, reaching a nearly constant value at the 16th day. The observed maximum concentrations (%w/w) were: 48.95% proteins, 2.88% xylose, 7.82% glucose, 4.54% arabinose, 8.28% fructose and 4.82% lipids. These values were only marginally affected by the type of treatment. Overall, the results obtained suggest that vinasse is a promising and sustainable medium for the growth of C. vulgaris and the production of valuable metabolites.

Gold nanoparticles (AuNPs) are currently under intense investigation for biomedical and biotechnology applications, thanks to their ease in preparation, stability, biocompatibility, multiple surface functionalities and size-dependent optical properties. The most commonly used method for AuNPs synthesis in aqueous solution is the reduction of tetrachloroauric acid (HAuCl₄) with trisodium citrate. We observed variations in the pH and concentration of the gold colloidal suspension synthesized under standard conditions, verifying a reduction in the reaction yield by around 46% from pH 5.3 (2.4 nM) to pH 4.7 (1.29 nM). Citrate-capped AuNPs were characterized by UV-visible spectroscopy, TEM, EDS and zeta-potential measurements, revealing a linear correlation between pH and the concentration of the generated AuNPs. This result can be attributed to the adverse effect of protons both on citrate oxidation and on citrate adsorption onto the gold surface, which is required to form the stabilization layer. Overall, this study provides insight into the effect of the pH over the synthesis performance of the method, which would be of particular interest from the point of view of large-scale manufacturing processes.

This study investigates distillery wastewater, commonly known as vinasse, as a potential culture medium for the production of Chlorella vulgaris and its most relevant metabolites. The effect of vinasse concentration on the composition of the biomass (proteins, carbohydrates and lipids) was evaluated in treatments performed in 6-L tubular air-lift reactors. The reactors were operated at 25 °C for 18 days, in total darkness, under a continuous flow of air. Results showed a rapid growth of microalgae in the first ten days, when an average production of 0.87 g/L was reached. Then, the daily biomass productivity began to decrease, up to an average value of 11.8 g/L at the 16th day. For all treatments, there was a significant reduction in the concentration of most metabolites in the first eight days. This was likely due to the adaptation of the biomass to the new conditions, with a the transition from autotrophic to heterotrophic metabolism. From the 10th day, the concentration of metabolites in the biomass began to increase, reaching a nearly constant value at the 16th day. The observed maximum concentrations (%w/w) were: 48.95% proteins, 2.88% xylose, 7.82% glucose, 4.54% arabinose, 8.28% fructose and 4.82% lipids. These values were only marginally affected by the type of treatment. Overall, the results obtained suggest that vinasse is a promising and sustainable medium for the growth of C. vulgaris and the production of valuable metabolites.

The aim of this work was to describe the physiological limitations induced under drought conditions in young sweet orange trees, including the crop capability to recuperate its physiological status once re-watering, and after a water withholding. The trial was conducted during two consecutive months (July and August) in two-years old sweet orange trees. Three irrigation treatments were arranged: A full irrigation treatment; (FI); a low-frequency deficit-irrigation treatment (LFDI); and a sustained-deficit irrigation (SDI) treatment. The obtained results showed that for Stem values below -1.5 MPa, significant decreases in gas exchange rates, evidencing diffusive limitations to drought stress. Additionally, there was evidence of increased osmolyte synthesis, compatible as a defensive response to prevent oxidative damage. Likewise, the isohydric behaviour observed also resulted in significant decreases in gs even for moderate stress situations. In addition, it was observed that in the LFDI treatment, the stress levels reached caused a significant increase in the levels of Pro and MDA, which were not equal to those detected in FI during the recovery periods, which leads us to assume that potential values below -1.8 MPa would be causing significant oxidative damage with no capacity for subsequent recovery, and probably affecting the final yield.

The production of vaccines of biological origin presents a tremendous challenge for researchers. In this context, animal cell cultures are an excellent alternative for the isolation and production of biologicals against several viruses since they have an affinity with viruses and a great capacity for their replicability. Different variables have been studied to know the system's ideal parameters, allowing it to obtain profitable and competitive products. Consequently, this work focuses its efforts on evaluating an alternative for producing an anti-influenza biological from MDCK cells using SuperPro Designer v8.0 software. The process uses the DMEN culture medium supplemented with nutrients as raw material for cell development; the MDCK cells were obtained from a potential scale-up with a final working volume of 500 L, four days of residence time, inoculum volume of 10%, and continuous working mode with up to a total of 7400 h/Yr of work. The scheme has the necessary equipment for the vaccine's production, infection, and manufacture with yields of up to 416,698 units/h. In addition, it was estimated to be economically viable to produce recombinant vaccines with competitive prices of up to 0.31 USD/unit.

Lycoriella species (Sciaridae) are responsible for significant economic losses in greenhouse production (e.g. mushrooms, strawberry, and nurseries). Current distributions of species in the genus are restricted to cold-climate countries. Three species of Lycoriella are of particular economic concern in view of their ability to invade across the Northern Hemisphere. We used ecological niche models to determine the potential for range expansion under climate change future scenarios (RCP 4.5 and RCP 8.5) in distributions of these species of Lycoriella. Stable suitability under climate change was a dominant theme in these species; however, potential range increases were noted for key countries (e.g. USA, Brazil, and China). Our results illustrate the potential for range expansion in these species in the Southern Hemisphere, including some of the highest greenhouse production areas in the world.

There is evidence of constitutional rank in Chile, and not only a sectoral rank, to estimate that the regulation of digital media is in an initial and insufficient phase to properly protect information pluralism as political pluralism. The study aims to investigate the forms of concentration, such as the communicational flow of digital media, to determine the opportunities and information defects of these media due to regulatory deficiencies in this sector. Data collection will be carried out through a qualitative and quantitative methodology. The prospect of the imminent constituent process in Chile provides the opportunity to the evaluate the possibilities to propose changes not only at the legislative level but also at the constitutional level, which are likely to benefit freedom of expression with greater guarantees to such as the pluralism of digital media. The latter also means assessing the relevance of enshrining the right to communication in the future.

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

A large diversity of epigenetic factors, such as microRNAs and histones modifications, are known to be capable of regulating gene expression without altering DNA sequence itself. In particular, miR-1 is considered the first essential microRNA in cardiac development. In this study, miR-1 potential role in early cardiac chamber differentiation is analyzed through specific signaling pathways. For this, we performed in chick embryos functional experiments by means of miR-1 microinjections into the posterior cardiac precursors -of both primitive endocardial tubes- committed to sinoatrial region fates. Subsequently, embryos were subjected to whole mount in situ hybridization, immunohistochemistry and RT-qPCR analysis. As a relevant nov-elty, our results revealed that miR-1 increases Tbx5, Gata4 and AMHC1, while this microRNA diminishes Mef2c expression, during early differentiation of cardiac sinoatrial region. Further-more, we observed in this developmental context that miR-1 upregulates CRABPII and RARß, and downregulates CRABPI, which are three crucial factors in retinoic acid signaling pathway. Interestingly, we also noticed that miR-1 directly interacts with HDAC4 and Calmodulin, as well as with Erk2/MAPK1, which are three key factors actively involved in Mef2c regulation. Our study shows, for the first time, a key role of miR-1 as an epigenetic regulator in early differenti-ation of cardiac sinoatrial region through orchestrating opposite actions between retinoic acid and Mef2c, fundamental to properly assign cardiac cells to their respective heart chambers. A better understanding of those molecular mechanisms modulated by miR-1 will definitely help in fields applied to therapy and cardiac regeneration and repair.

We investigate some of the fundamental features of the interaction of mixed kaleidoscope states, namely, particular statistical mixtures of coherent states, with two-level atoms in the Jaynes-Cummings model framework. We begin our analysis by calculating the von Neumann entropy of the field which is determined with help of the virtual atom method. Oscillations appear in this entropy that indicate a state of purity greater than the initial state, {it i.e.}, a purification of the initial state is achieved. In this oscillatory region, we obtain the field Wigner function that resembles Schrodinger's cats.

A novel method based on a hybrid incremental modeling approach has been designed and applied to imbalance detection in ultra-high precision rotating machines. The model is obtained by a two-step iterative process that combines an overall model (least-squares fitting) with a local model (fuzzy k-nearest-neighbour) to take advantage of their complementary capacities. Three normalization strategies of evaluating the effect on accuracy are analyzed. A comparative study demonstrates that the hybrid incremental model provides better error-based performance indices for detecting imbalance than a nonlinear regression model and an adaptive neural-fuzzy inference system model. The suitability of Mahanolobis normalization for hybrid incremental modeling is also demonstrated in this case study. The proposed strategy for imbalance detection is simple, fast, and non-intrusive, reducing the deterioration in the performance of ultra-high precision rotating machines due to vibrations.

Monitoring complex electro-mechanical processes is not straightforward despite the arsenal of techniques nowadays availanle. This paper presents a method based on Adaptive-Network-based Fuzzy Inference System (ANFIS) to estimate eccentricity of its spinning axis. The method is experimentally tested on an ultra-precision rotating device commonly used for micro-scale turning. The developed model has three inputs, two obtained from a frequency domain analysis of a vibration signal and the third, which is the device rotation frequency. A comparative study demonstrates that an adaptive neural-fuzzy inference system model provides better error-based performance indices for detecting imbalance than a non-linear regression model. This simple, fast, and non-intrusive imbalance detection strategy is proposed to counteract eventual deterioration in the performance of ultra-high precision rotating machines due to vibrations.

Opossums, native to the Americas, are unique marsupials with over 100 species. The Common Opossum and Virginia Opossum are notable species. They are nocturnal, omnivorous, and adapt to various habitats. Their reproduction involves a short gestation and marsupial pouch development. Despite their ecological benefits like seed dispersal and insect control, their proximity to human habitats exposes them to pathogens, posing public health risks. These include protozoa, helminths, and arthropods that can spread zoonotic parasites and vector-borne diseases. The marsupial immune system, including opossums, is complex, rivaling eutherian mammals. Key immune genes were identified in the grey short-tailed opossum genome. CD1 protein and VpreB surrogate light chain were also found. Marsupials are proposed as ideal models for studying developmental immunology. A West Indian opossum (Didelphis marsupialis) was found and examined. Blood tests revealed abnormalities, including a low white blood cell count and signs of anemia. The results contribute to understanding the species’ health and adaptability in the wild.

Pseudomonas aeruginosa is an opportunistic pathogen, especially dominant in people with cystic fibrosis; the drug resistance expressed by this pathogen and its capacity for adaptation generate a great challenge for its treatment and control, increasing morbidity and mortality rates globally. In this sense, the search for new treatment alternatives is imminent today, with products of plant origin being an excellent alternative to be used. The objective of this research was to evaluate the antibacterial and antibiofilm potential and to explore the possible effect of ethanolic extracts of wood and bark of Duguetia vallicola on the cell membrane. Microdilution assays showed inhibition of bacterial growth by more than 50%, with the lowest concentration evaluated (62.5μg/mL) of both extracts. Furthermore, we report the ability of both extracts to inhibit mature biofilms, with inhibition percentages between 48.4% and 93.7%. Intracellular material leakage experiments (260/280 nm), extracellular pH measurement, and fluorescence microscopy with acridine orange (AO) and ethidium bromide (EB) showed cell membrane damage. This indicates that the anti-bacterial action of ethanolic extracts of D. vallicola is associated with damage to the integrity of the cell membrane and consequent death of these pathogens. These results serve as a reference for future studies in establishing the mechanisms of action of these extracts.

Severe combined immunodeficiency (SCID) is a primary inherited immunodeficiency that could be fatal, usually due to opportunistic infections caused by bacteria, viruses, fungi, and protozoa if left untreated. Opportunistic infections are the most common presentation of SCID these include viral, fungal, or intracellular bacteria, and infection should prompt immunological investigation. This review aimed to provide a comprehensive approach to the microrganisms associated with severe combined immunodeficiency (SCID) and its management. The authors described SCID as a syndrome and summarized the different microorganisms that affect children and how they are managed.

In this paper, we introduce Syntax-Enhanced Transformer Model (SET), a groundbreaking approach in the realm of Transformer-based language modeling that seeks to redefine the boundaries of linguistic analysis and comprehension. SET innovatively combine (i) the well-established high-level performance, scalability, and adaptability of traditional Transformers with (ii) a sophisticated analysis of syntactic structures. This synergy is enabled by a novel attention mechanism tailored to parse syntactic nuances and a deterministic process adept at transforming linearized parse trees into meaningful linguistic representations. Our comprehensive experiments reveal that SET significantly advance the field by surpassing existing benchmarks in sentence-level language modeling perplexity. They exhibit exceptional proficiency in tasks that require an acute awareness of syntax, setting new standards for language models in understanding complex linguistic structures. Furthermore, SET demonstrate an enhanced capability to grasp nuanced linguistic patterns that have traditionally been challenging for standard Transformer models. However, our studies also uncover a unique aspect of SET: while they excel in sentence-level tasks, their representation of sentences as singular vectors—owing to the syntactic composition constraints intrinsic to their design—introduces certain limitations in document-level language modeling. This observation points to an intriguing area for future exploration; it suggests the potential need for an alternative or complementary memory mechanism within Transformer models, one that functions independently from, yet in harmony with, syntactic structures. Such a mechanism could be pivotal in enhancing the model's ability to comprehend and process long-form texts effectively. In conclusion, SET mark a significant stride in the journey towards more sophisticated, syntax-aware language models. They offer promising insights into the integration of deep linguistic knowledge with cutting-edge machine learning techniques, potentially opening doors to a new era of natural language understanding and processing.

The paradigm of leveraging code as a dataset has recently gained traction, offering innovative solutions in domains such as automated commit message generation, pull request description automation, and program repair mechanisms. Consider the challenge in generating commit messages: traditional methods treat source code as a mere token sequence, applying neural machine translation models. This approach, however, overlooks the critical syntactic structures inherent in programming languages, which could offer deeper insights and improved accuracy. Building upon prior research, specifically the Code2Seq framework, which utilized Abstract Syntax Tree (AST) structural data for source code representation to automate method name generation, this paper extends and refines this concept. We introduce "CSR", a novel methodology adapted to represent code edits effectively. This paper investigates the impact of employing syntactic structure, focusing on the classification of code edits. Drawing inspiration from Code2Seq, "CSR" utilizes AST's structural properties, particularly the paths connecting leaf nodes, to enhance the task of code edit classification. This approach is rigorously evaluated on two distinct datasets, comprising fine-grained syntactic edits. Our comprehensive experiments reveal that incorporating syntactic structures does not significantly outperform simpler methodologies. While methods like Code2Seq and our proposed "CSR" show potential, our findings highlight that there is considerable scope for improvement and refinement before such techniques can be universally applied for learning representations of code edits. We anticipate that our findings will spark further research in this field, paving the way for more effective use of syntactic structures in code representation.

Contemporary advanced models for aspect-targeted opinion word extraction (ATOWE), which predominantly utilize BERT-based encoders at a word level, have shown limited advancements when integrated with graph convolutional networks (GCNs) for syntactic tree assimilation. Recognizing the prowess of BERT subwords in encapsulating rare or context-poor words, this study pivots from syntactic trees to BERT subwords, omitting GCNs from the structural framework. Our approach, named Aspect-Enhanced Wordpiece Extraction Model (AEWEM), focuses on refining aspect representation during encoding. We propose an input format of paired sentence-aspect, diverging from traditional single-sentence inputs. AEWEM demonstrates superior performance on benchmark datasets, establishing a robust foundation for future explorations in this domain.

The Transformer architecture, while adept at capturing context through self-attention, falls short in encapsulating complex syntactic structures effectively. Addressing this gap, we introduce the Linguistic Structure through Graphical Interpretation with BERT (LSGIB) approach in Machine Translation (MT) frameworks. Combining the strengths of Graph Attention Network (GAT) and BERT, LSGIB intricately captures syntactic dependencies as explicit knowledge from the source language. This enhances the source language representation and aids in more accurate target language generation. Our empirical analysis leverages gold-standard syntax-annotated sentences and employs a Quality Estimation (QE) model. This approach enables us to assess translation improvements in terms of syntactic accuracy, extending beyond traditional BLEU score metrics. The LSGIB model demonstrates superior translation quality across diverse MT tasks, maintaining robust BLEU scores. Our study delves into the optimal sentence lengths benefiting from LSGIB and identifies which syntactic dependencies are more precisely captured. We observe that GAT's ability to learn specific dependency relations directly influences the translation quality of sentences with those relations. Additionally, we discover that incorporating syntactic structure into BERT's intermediate and lower layers offers a novel approach to modeling linguistic structure in source sentences.

The field of program classification, a critical aspect of software engineering, facilitates understanding and categorization of code across various applications, including anomaly detection, and code quality assessment. The advancement of cross-language program classification opens up avenues for efficient code translation among different programming languages, significantly aiding developers in rapid coding and reducing development cycles. Existing research primarily focuses on semantic code analysis, with limited emphasis on cross-linguistic challenges. To address this, we introduce an innovative neural network model, CodeSemanticsNN, which leverages a refined Syntax Structure (SS) approach. This model consists of two integral mechanisms: first, it adopts a novel SS representation that combines sequential and graph-based SS structures, enhancing semantic feature capture. Second, it employs a 'unified vocabulary' strategy to bridge the gap between diverse programming languages, facilitating efficient cross-language classification. Additionally, we have compiled a comprehensive dataset of 20,000 files spanning five programming languages, serving as a benchmark for cross-language classification. Our experiments on this dataset demonstrate that CodeSemanticsNN surpasses existing models in four key metrics: Precision, Recall, F1-score, and Accuracy.

The evolution of sentence representation learning, especially with parse tree encoders, has shown remarkable progress. Traditional approaches predominantly rely on recursive encoding of tree structures, which impedes parallel processing capabilities. Additionally, these methods often overlook the significance of dependency tree arc labels. To overcome these limitations, we introduce the Syntax-Enhanced Transformer (SET), incorporating a novel dual-attention mechanism that integrates relation-focused attention alongside traditional self-attention. This design effectively encodes both dependency and spatial positional relationships within sentence dependency trees. Our approach innovatively incorporates syntactic information into the Transformer framework without compromising its inherent parallelizability. The SET demonstrates superior or comparable performance to contemporary methods across various sentence representation tasks, significantly enhancing computational efficiency.

This paper introduces a novel graph polynomial approach for differentiating tree structures in dependency grammar. Utilizing this polynomial representation, we develop a metric to assess the similarity in syntax. This approach offers a detailed and inclusive analysis of the dependency structures and relationships in sentence construction. We employ this polynomial method to examine sentence structures across various languages in the Parallel Universal Dependencies treebanks. Our analysis includes comparing the syntax of original sentences and their translated counterparts in diverse languages, alongside a comprehensive study of syntactic typologies within these treebanks. Additionally, we explore the application of our methodology in evaluating the syntactic diversity within language corpora.

Recent advancements in neural language models, particularly attention-based architectures like the Transformer, have substantially surpassed traditional methods in various natural language processing tasks. These models adeptly generate nuanced token representations by considering contextual relations within a sequence. However, augmenting these models with explicit syntactic knowledge, such as part of speech tags, has been found to remarkably bolster their effectiveness, especially under constrained data scenarios. This study introduces the Linguistic Enhanced Transformer (LET), which integrates multiple syntactic features, showing a notable increase in translation accuracy, evidenced by an improvement of up to 1.99 BLEU points on subsets of the WMT '14 English-German dataset. Furthermore, this paper demonstrates that enriching BERT models with syntax-aware embeddings enhances their performance on several GLUE benchmark tasks.

Conventional text style transfer (TST) methodologies primarily utilize style classifiers to segregate the content and stylistic elements of text for effective style transformation. Despite the pivotal role of these classifiers, their influence on TST techniques remains largely unexplored. This study embarks on a detailed exploration of the limitations inherent in style classifiers within current TST frameworks. We reveal that these classifiers often inadequately comprehend sentence syntax, leading to diminished performance in TST models. In response, we introduce the Syntax-Enhanced Style Transfer (SEST) model, a groundbreaking approach incorporating a syntax-sensitive style classifier. This classifier ensures that the extracted style representations robustly encapsulate syntax nuances, enhancing TST effectiveness. Rigorous evaluations across diverse TST benchmarks demonstrate that SEST significantly surpasses contemporary models in performance. Additionally, our case studies highlight SEST's proficiency in producing syntactically coherent sentences that aptly retain original content.

Air pollution includes particle-bound Polycyclic Aromatic hydrocarbons (PAHs) which eventually reach the placenta triggering adverse perinatal outcomes by long-term exposure. Late-ly, air pollution has increased over the Metropolitan Area of Medellin-Colombia (MAMC) but its effects on pregnancy are still unknown. In this research, we made a real-time analysis of airborne total PAHs using a photoelectric sensor for residential places influenced by industrial and traffic sources contrasting southern and northern MAMC during the second peak of the bimodal ten-dency for PM2.5 emissions in this region. Additionally, we analyzed individual PAHs by GC/MS coupled to pressurized hot water extraction methodology. Data was applied in an Inhalation In-take Model to assess pregnancy exposure. The average concentration of PAHs over southern MAMC was three times higher than over northern MAMC where the abortion rate has been 1.4 times higher presented in database. Previous research found that PAHs act as an Endo-crine-Disrupting Chemical (EDC) during pregnancy and even heavy congeners could reside in umbilical cord blood. Finally, the annual series of abortion rates in the MAMC showed a signifi-cant correlation with the annual average levels of PM2.5 which are associate to PAHs. Although this significant correlation does not imply causality, our results suggest an important connection between both variables. This latter finding opens a gap in deeply understanding how regions with high PAHs-convergence influences abortion rates in MAMC.

The main purpose of the study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (n=56; 11.73 ± 1.4 years old) com-pared to a workout based on general strength training. Eight-week training program was im-plemented, with four sessions per week and two-hours per session. Sample was divided in two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the compe-tition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the ex-perimentation. The results show that, although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94W) obtained better averages in all phases of the study compared to the CG (+5.88W). Furthermore, this increase was greater in male rowers (+ 34.06W) than in female rowers (+24.54W). These results reveal that a specific rower rowing ergometer training program has a significant effect than a general strength program and these effects can even be observed a year after the intervention.

The main objective of this work is the design and implementation of self-adaptive capabilities in wireless sensors by applying control engineering and model-based design methodologies. It has been addressed the problem related to the changes in the flow of data packets through the network connection and the excess energy consumption that this causes in these devices. To design the solution, a systemic characterization of the scheduling and execution process of embedded tasks on the device has been carried out. This means defining cause-effect relationships in the system and its modelling theoretically and/or experimentally. In turn, these models facilitate the design of control strategies to improve the dynamic behavior of the system. As a solution, a self-adaptation strategy based on feedforward control algorithm has been designed and developed, which has been applied to improve the dynamic behavior and resource consumption. The developed solution has been satisfactorily evaluated experimentally.

An exploratory Life Cycle Assessment was carried out to provide insight into the environmental impacts of using the green seaweed Ulva spp. as a feedstock for production of bioplastic. The study focused on the production of lactic acid as a precursor of polylactic acid. The studied production process consists of (1) the cultivation of Ulva spp. in Integrated Multitrophic Aquaculture, (2) the processing of the biomass for solubilisation of sugars, (3) the fermentation of the sugars to lactic acid and (4) isolation of lactic acid from the fermentation broth. The study identifies environmental hotspots and compares the experimental seaweed production chain with conventional feedstock. The main hotspot identified is electricity consumption during seaweed cultivation. This impact of electricity consumption can be lowered by reducing energy use and sourcing renewable energy, and by improving the material efficiency in the product chain. To improve understanding of the environmental impacts of the production process, future studies can broaden the system boundaries and broaden the scope of sustainability issues included in the environmental assessment.

During the last 100 years the planet has increased its temperature rapidly, this climate change could bring catastrophic effects for organisms and natural systems. One of the most affected groups is the ectotherms, due to their direct dependence on the environmental temperature. In recent years several studies analyse the effects of temperature and the thermal tolerance on several species of ectotherms. However, there are species whose thermal tolerances are still unknown. Such is the case of critically endangered species the Montseny Brook Newt (Calotriton arnoldi), endemic from the Montseny massif in Spain and whose thermal biology is unknown. Its critical situation makes essential to know its tolerance to cooling, warming and thermopreferendum in water environment where the newt lives. Three experimental procedures were conducted from the western and eastern subpopulations of C. arnoldi considering four classes separately (males, females, juveniles and larvae). The results obtained showed that the CTmax of the species exceeded 31°C, with a significant difference between the two populations. We found that the species tolerates well low temperatures (<1°C), because of the genera Calotriton is adapted to lives in cold waters with temperatures below 15º. Although the thermopreference of the species was expected to trend to cold temperatures, some individuals chose relatively high temperatures, obtaining a range of 11.7°C to 21.6°C. The results presented in this study are an advance in the knowledge of the thermal physiology of this species and support the importance of the temperature of the torrent on its survival. Knowing their thermal limits and their preferred temperature range will help to propose management measures that promote the conservation of streams and its riparian forest cover to mitigate the temperature increase due to climate change.

In this paper, experimental results about the performance of a Takagi-Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration for the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. The Takagi-Sugeno Fuzzy Model (TSFM) design comes from linearization of the nonlinear model around two operation points near from the upright position of the EV3BRS's body. The Parallel Distributed Compensation (PDC) approach is used to the design of the TSFC. The Linear Matrix Inequalities (LMIs) approach is used to get the feedback gains for every local linear controller guaranteeing global asymptotically stability, via a more relaxed stability condition, of the overall fuzzy control system. Measurement and control data from and to the EV3BRS are transferred via telecontrol and telemetry.

Gymnophiona, the most poorly known group of extant amphibians, includes elongated limbless tetrapods, with compact ossified skulls and reduced eyes, mainly adapted to fossorial life (only the Typhlonectidae exhibits adaptations for an aquatic or semiaquatic behavior). Caecilians are poorly represented in the fossil record, and despite the low number of fossil specimens described until now (only four taxa, in addition to indeterminate fragmentary material), their fossils play a key role in the knowledge of Lissamphibia origin and evolution, as well as contribute directly to a better understanding of phylogeny, taxonomy and biogeography of extant gymnophionan taxa. These records are scattered throughout geological time (from the Jurassic to the Neogene) and space (they are represented only on North and South America and Africa). Here, we revisit the caecilian fossil record, providing a brief description of all known extinct taxa described so far, along with general remarks about their impact on systematics, time range and geographic distribution of the clade, as well as prospects for future research. Possible calibration constraints based on the caecilian fossil record are provided.

One of the most effective image processing techniques is the use of convolutional neural networks, where we combine intensity values at grid points in the vicinity of each point. To speed up computations, researchers have developed a dilated version of this technique, in which only some points are processed. It turns out that the most efficient case is when we select points from a sub-grid. In this paper, we explain this empirical efficiency proving that the sub-grid is indeed optimal – in some reasonable sense. To be more precise, we prove that all reasonable optimality criteria, the optimal subset of the original grid is either a sub-grid, or a sub-grid-like set.

Most works related to the identification of mathematical nonlinear systems make one suppose that such approaches can always be directly applied to any nonlinear system. This misconception produces a great deal of discouragement when the obtained results are not the expected ones. Thus, the current work hypothesizes that the most information one has about the mathematical structure of the model, the most precise the identification result should be. Therefore, a variant of the Sparse Identification of Nonlinear Dynamics (SINDY) approach is presented to obtain the full mathematical nonlinear model of a high-order system with coupled dynamics, namely, a commercial quadcopter. Furthermore, due to its high sensitivity to inputs, a control system is devised using the identified model to stabilize the quadcopter. This illustrates the effectiveness of the proposed identification method.

The Covid-19 crisis has been one of the most relevant economic shocks in the history of the modern economy, mainly due to the restrictions on travel and social interaction taken by the authorities (quarantines, closure of schools, artistic activities, bars, and restaurants, capacity in stores), to reduce the transmission of the virus (Sars-Cov2), having consequences on the national productions of all countries (about 7% for the loss of GDP worldwide). In our study, we analyze, through clustering methods, the effects of the level of contagion, economic projections, and economic mitigation measures taken by governments for managing the pandemic. According to the analyses, it can be concluded that a low infection rate implies a lower loss of product and economic savings when applying economic mitigation measures, taking relevance in the management of sanitary measures to reduce the transmission of the virus (and the temporality of these).

I. Introduction: Adherence to ART reduces morbidity and mortality among PLHIV by suppression of viral replication, restoration and preservation of immune function. However, poor adherence may lead to treatment failure and death. PLHIV have high probability of treatment interruptions due to lockdowns related to COVID-19 protocol. Mortality rate is higher among COVID-19 patients with HIV than those with COVID-19 only. This led to determination of the barriers to antiretroviral medication adherence in PLHIV at the time of COVID-19 pandemic and seek significant association between identified HIV treatment barriers and socio-demographic characteristics. II. Methods: A cross-sectional study using online survey questionnaire was distributed via social media. Sample size was computed using Open Epi software. Data was analyzed using Stata software. Categorical variables and quantitative data were summarized using frequencies and percentages, and mean and standard deviation respectively. Chi-square test or Fisher’s exact test, whichever is more appropriate, was used to determine association between socio-demographic characteristics and HIV treatment barriers. III. Results: There is a total of 116 respondents, 115 were males, homosexual (59.5%), with mean age of 30.25 years old (SD = 6.22) and majority (53.4%) were from NCR. The most common HIV treatment barriers reported by PLHIV in accessing treatment and care were unavailability of transportation and cost of courier services for ARV delivery (62.1%), location of treatment hubs (52.6%) and financial assistance (37.9%). IV. Conclusion: There is significant association between location of treatment hubs and respondents who finished college/graduate studies; checkpoints and crossing borders and: 1. respondents from Northern Luzon, 2. unemployment; financial assistance and: 1. Respondents 18 to 25 years old, 2. unemployment, 3. respondents who finished elementary/high school; psychosocial support and: 1. Respondents from NCR, 2. Respondents 26 to 30 years old;

Structural deformations are one of the most significant factor that affects machine tool (MT) positioning accuracy. These induced errors are complex to be represented by a model, nevertheless they need to be evaluated and predicted in order to increase the machining performance. This paper presents a novel approach to calibrate a machine tool in real-time, analyzing the thermo-mechanical errors through Fibre Bragg Grating (FBG) sensors embedded in the MT frame. The proposed configuration consists of an adaptronic structure of passive materials, Carbon Fibre Reinforced Polymers (CFRP), equipped by FBG sensors that are able to measure in real-time the deformed conditions of the frame. By using a proper thermo-mechanical kinematic model, the displacement of the end effector may be predicted and corrected when it is subjected to external undesired factors. By starting from a set of FE simulations to develop a model able to describe the MT structure stresses, a prototype has been fabricated and tested. The scope was to compare the numerical model with the experimental tests using FBG sensors. The experimental campaign has been performed varying the structure temperature over time and measuring the tool tip point (TTP) positions. The obtained results showed a substantial matching between the real and the predicted position of TTP confirming the effectiveness of the proposed calibration system.

Improving performance and promoting sustainability in women's handball are key objectives to maximize the potential of female players and ensure the long-term viability of the sport. In this context, training with Olympic movements and their derivatives improves the development of strength, power, and speed, which are determinants of performance in team sports. The aim of this study was to determine if training with Olympic movements produces significant improvements in jumping, throwing, sprinting, and change of direction performance in women handball players. Twenty-one female handball players participated in the study (10 for the control group and 11 for the intervention group). Age ranged from 15 to 17 years. All participants performed four assessment tests (Abalakov Test, throw test, 20-meter Sprint and V-Cut Test) to determine jump height, throwing speed, running speed, and change of direction ability. Measurements were carried out before and after the intervention. For six weeks, the control group performed the strength work established by the club twice a week while the intervention group additionally performed training with Olympic movements. Significant differences (p <0.05) were found between the pre and post measurement of the control group and the intervention group in jump height, throwing speed and running speed, being higher in the intervention group. For the change of direction, no significant differences were found. Between groups, significant differences were observed at the end of the intervention for jump height and running speed. The conclusion of this study was that, by training with Olympic movements, in addition to regular training, could produce greater improvements in jumping performance, throwing speed and running speed in female handball players.

Earthquakes are one of the most catastrophic natural phenomena. After an earthquake, earthquake reconnaissance enables effective recovery by collecting building damage data and other impacts. This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. We have reviewed 38 articles that indicate the sources used by different authors to collect data related to damage and post-disaster recovery progress after earthquakes between 2014 and 2021. The current data collection methods have been grouped into seven categories: fieldwork or ground surveys, omnidirectional imagery (OD), terrestrial laser scanning (TLS), remote sensing (RS), crowdsourcing platforms, social media (SM) and closed-circuit television videos (CCTV). The selection of a particular data source or collection technique for earthquake reconnaissance includes different criteria depending on what questions are to be answered by this data. We conclude that modern reconnaissance missions can not rely on a single data source and that different data sources should complement each other, validate collected data, or systematically quantify the damage. The recent increase in the number of crowdsourcing and SM platforms used to source earthquake reconnaissance data demonstrates that this is likely to become an increasingly important source of data.

Previous studies have reported certain sex differences in motor performance precision. The aim of the present study was to analyse sex differences in fine motor precision performance for both hands in different tests conditions. 220 Spanish participants (ages: 12-95) performed fine motor tasks - tracing over the provided models – lines of 40 mm for both hands, two sensory conditions (PV – proprioceptive-visual; P – proprioceptive only) and three movement types (F – frontal, T – transversal and S - Sagittal). Differences in line length (the task focused on precision) were observed through MANOVA analysis for all test conditions, both sexes and different age groups. Sex differences in precision were observed in F and T movement types (statistically significance level and higher Cohens’ d was observed in condition with vision). No any statistically significant differences were observed in both hands and sensory conditions in sagittal type. Sex differences in fine motor precision were more frequently observed in the PV sensory condition in the frontal movement type and less in the sagittal one.

Clusterin (CLU) protein is involved in various pathophysiological processes including carcinogenesis and tumor progression. In recent years, the role of the secretory isoform has been demonstrated in tumor cells, where it inhibits apoptosis and favors the acquisition of resistance to conventional treatments used to treat cancer. To determine the possible therapeutic potential of inhibiting this protein, numerous studies have been carried out in this field. In this paper, we show the existing knowledge on the inhibition of this protein in different types of cancer and discuss the importance it could have in the development of new therapies directed against this pathology.

The FOLFOX scheme, based on the association of 5-fluorouracil and oxaliplatin, is the most frequently indicated chemotherapy scheme for patients diagnosed with metastatic colorectal cancer. Nevertheless, development of chemoresistance is one of the major challenges associated with this disease. It has been reported that epithelial-mesenchymal transition (EMT) is implicated in microRNA-driven modulation of tumor cells response to 5-fluorouracil and oxaliplatin. Besides, from pharmacogenomic research it is known that overexpression of genes encoding dihydropyrimidine dehydrogenase (DPYD), thymidylate synthase (TYMS), methylenetetrahydrofolate reductase (MTHFR), the DNA repair enzymes ERCC1, ERCC2, and XRCC1, and the phase 2 enzyme GSTP1 impair the response to FOLFOX. It has been observed that EMT is associated with overexpression of DPYD, TYMS, ERCC1, and GSTP1. In this review we investigated the role of miRNAs as EMT promotors in tumor cells, and its potential effect on upregulation of DPYD, TYMS, MTHFR, ERCC1, ERCC2, XRCC1 and GSTP1 expression, which would lead to resistance of CRC tumor cells to 5-fluorouracil and oxaliplatin. This constitutes a potential mechanism of epigenetic regulation involved in late-onset of acquired resistance in mCRC patients under FOLFOX chemotherapy. Expression of these biomarkers microRNA could serve as tools for personalized medicine, and as potential therapeutic targets in the future.

Background and Objectives: The techniques directed to the cranial field in osteopathy are the most questioned due to the lack of scientific evidence. In osteopathic practice, manual palpation is essential and, therefore, measuring reliability is fundamental. The objective of study is to assess the reliability and validity of osteopathic treatment depending on experience. Materials and Methods: A cross-sectional study of reliability and validity was conducted. For measurements, a strain gauge was placed on the sphenobasilar synchondrosis of the skull base, and three maneuvers (lateral compression, anteroposterior compression and compression maneuver of the mastoids) were repeated 25 times each by osteopaths with different time of experience (5-10 years, 1-5 years, <1 year). Measurement averages were computed for each of the three maneuvers to verify the average effect of each group in comparison to that of the Gold Standard (GS) (>10 years of experience). Data were analyzed to check for inter- and intra-observer reliability using intra-class correlation coefficients (ICC). Results: Reliability and validity in 5-10 experience of observer 1 and observer 2 in the tree maneuvers was excellent (p<0.001) against GS. Poor or enough reproducibility and concordance were observed in osteopaths with less experience. Conclusion: Experience of osteopaths determines the efficacy of cranial maneuvers in osteopathic treatment for patients’ rehabilitation.

Soot combustion experiments with 5%O2/He were conducted using model soot, and four distinct compositions of CexPr1-xO2-δ oxides were prepared, varying nominal cerium com-positions (x=0, 0.2, 0.3, and 1). The catalyst samples were comprehensively characterized using techniques such as XRD, Raman spectroscopy, HR-TEM, N2 adsorption at −196 °C, XPS, O2-TPD, H2-TPR, and work function measurements. The Pr-rich compositions, rang-ing from Ce0.3Pr0.7O2-δ to PrO2-δ, resulted in a significant increase in the total evolved O2 amounts and enhanced catalyst reducibility. However, a decrease in textural properties of the catalysts was noted, being particularly important for the pure praseodymia under the synthesis route conducted. The catalytic activity was investigated under two contact modes of mixing between soot and catalyst: loose and tight. The results revealed that the catalytic performance is associated with the surface contact in tight contact mode and with the combination of surface/subsurface/bulk oxygen mobility and the BET surface ar-ea in loose contact mode. Notably, the T10 and T50 parameters were achieved at much lower temperatures than the uncatalyzed soot combustion, even under loose contact conditions. Specifically, the 50% conversion was achieved at 511℃ and 538℃ for Ce0.3Pr0.7O2 and Ce0.2Pr0.8O2, respectively. While no direct correlation between catalytic activity and work function was observed a significant relationship emerges between work function values and the formation of oxy-gen vacancies, whatever the conditions used for these measurements. On the other hand, the ability to generate a high population of oxygen vacancies at low temperatures, rather than the direct activation of gas-phase O2, influences the catalytic performance of Pr-doped ceria catalysts, highlighting the importance of surface/subsurface oxygen vacancy generation, which was the parameter which showed better correlation with the catalytic activity, whatever the soot conversion value or the mode of contact considered.

The theory and working principle of fabric phase sorptive extraction (FPSE) is presented that eloquently explains the mystery behind this new and powerful sample preparation technique. FPSE innovatively integrates the benefits of sol-gel coating technology and the rich surface chemistry of cellulose/polyester/fiberglass fabric, resulting in a microextraction device with very high sorbent loading in the form of an ultra-thin coating. This porous sorbent coating and the permeable substrate synergistically facilitate very fast extraction equilibrium. The flexibility of the FPSE device allows for direct insertion into original, unmodified samples of different origin. Strong chemical bonding between the sol-gel sorbent and the fabric substrate permits the exposure of FPSE devices to any organic solvent for analyte back-extraction/elution and to highly acidic or basic environments (pH 1-12) if required. A sol-gel derived sorbent, highly polar sol-gel poly(ethylene glycol) coating, was generated on cellulose substrates. Five cm2 segments of these coated fabrics were used as the FPSE devices for sample preparation using direct immersion. An important class of environmental pollutants, substituted phenols, was used as model compounds to evaluate the extraction performance of FPSE. The high primary contact surface area (PCSA) of the FPSE device and porous structure of the sol-gel coatings resulted in very high sample capacities and incredible extraction sensitivities for both the compound classes in a relatively short period of time. Different extraction parameters were evaluated and optimized. The new extraction devices demonstrated part per trillion level detection limits for substituted phenols, a wide range of detection linearity, and good performance reproducibility.

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual energy imaging remains relatively untapped, possibly due to its intricate workflow and intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is neces-sary for an appropriate clinical use. The aims of this paper are to review physical and technical basis of DECT acquisition and analysis, to discuss advantages and limitations of DECT in dif-ferent clinical scenarios, to review technical constraints in material labeling and quantification, and to evaluate cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radioge-nomics

The art of representing source code is pivotal in numerous programming analysis applications. Recent strides in neural networks have marked notable successes in this realm. However, the peculiar structural characteristics inherent in programming languages have not been fully exploited in existing models. While neural models based on abstract syntax trees (ASTs) adeptly manage the tree-like nature of source codes, they fall short in discerning the diverse substructural nuances within programs. This paper introduces the Dynamic Syntax Tree Model (DSTM), an innovative approach that fuses various neural network modules into tree architectures tailored to the specific AST of the input. Distinct from preceding tree-based neural models, DSTM adeptly discerns the semantic variances across different AST substructures. We validate DSTM through rigorous testing in program classification and code clone detection, outperforming contemporary methods and demonstrating the benefits of harnessing intricate source code structures.

QPEs (Quantitative Precipitation Estimates) obtained from remote sensing or ground-based radars could complement or even be an alternative to rain gauge readings. However, to be used in operational applications, a validation process has to be carried out, usually by comparing their estimates with those of a rain gauges network. In this paper, the accuracy of two QPEs are evaluated for three extreme precipitation events in the last decade in the southeast of the Iberian Peninsula. The first QPE is PERSIANN-CCS, a satellite-based QPE. The second is a meteorological radar with Doppler capabilities that works in the C band. Pixel-to-point comparisons are made between the values offered by the QPEs and those obtained by two networks of rain gauges. The results obtained indicate that both QPEs were well below the rain gauge values, especially in extreme rainfall time slots. There seems to be a weak linear association between the value of the discrepancies and the precipitation value of the QPEs. It does not seem that radar is more accurate than PERSIANN-CCS, despite its larger spatial resolution and its commonly higher effectiveness. The main conclusion is that neither PERSIANN-CCS nor radar, without empirical calibration, are acceptable QPEs for the real-time monitoring of meteorological extremes in the southeast of the Iberian Peninsula.

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine learning classifiers and regressors and evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to dif- ferent results, with deep neural networks (DNNs) on user-defined physicochemically-relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically-based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evalu- ation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and predic- tion, improving assessment and design of compounds. Source code and data are available at https://github.com/AlfonsoTGarcia-Sosa/ML

Tourism is the main economic sector in the Balearic Islands (Spain) and hotel housekeepers (HHs) are a large occupational group, in which stress is becoming a major issue. This study aims at exploring in-depth factors perceived as stressors by HHs and key-informants, and their effects on work-life balance (WLB). A qualitative design with phenomenological approach was used, conducting six focus groups with 34 HHs and 10 individual interviews with key-informants. Results were analyzed adopting the job demands-resources model and a gender perspective. High demands –e.g work overload, time pressure, physical burden...-, lack of enough resources and little control –derived from role conflict, unexpected events...- were the most important factors explaining HHs’ stress. Additionally, this imbalance was perceived as leading to health problems –mainly musculoskeletal disorders-. Working schedule was mentioned as a facilitator to WLB, whereas an imbalance between job demands and resources led to work-home conflict –preventing them from enjoying leisure time-. Multiple roles at work and at home increased their stress. HHs experienced their job as invisible and unrecognised. Regarding practical implications, our recommendations for hotel organization include reducing workload and increasing resources, which would improve the job demands-resource balance, diminish negative mental and physical outcomes and improve WLB.

Endophytic insect pathogenic fungi have a multifunctional lifestyle; in addition to its well-known function as biocontrol agents, it may also help plants respond to other biotic and abiotic stresses, such as iron (Fe) deficiency. This study explores M. brunneum EAMa 01/58-Su strain attributes for Fe acquisition. Firstly, direct attributes include siderophore exudation (in vitro assay) and Fe content in shoots and in the substrate (in vivo assay) were evaluated for three strains of Beauveria bassiana and Metarhizium bruneum. The M. brunneum EAMa 01/58-Su strain showed a great ability to exudate iron siderophores (58.4% surface siderophores exudation) and provided higher Fe content in both dry matter and substrate compared to the control and was therefore selected for further research to unravel the possible induction of Fe deficiency responses, Ferric Reductase Activity (FRA), and relative expression of Fe acquisition genes by qRT-PCR in melon and cucumber plants.. In addi-tion, root priming by M. brunneum EAMa 01/58-Su strain elicited Fe deficiency responses at transcriptional level. Our results show an early up-regulation (24, 48 or 72 h post inoculation) of the Fe acquisition genes FRO1, FRO2, IRT1, HA1, and FIT as well as the FRA. These results highlight the mechanisms involved in the Fe acquisition as mediated by IPF M. brunneum EAMa 01/58-Su strain.

This work is based on identifying the analysis techniques used to evaluate the antioxidant and anti-inflammatory effects using the zebrafish model. In this context, a literature review was performed with the Web of Science database. We used the terms zebra fish, antioxidant, anti-inflammatory, model, and Danio rerio. Fifty articles were reviewed, of which thirty-three were chosen to perform this review and were classified according to the source of plant extracts, compounds extracted from plants, chemical compounds, and other sources. This paper is an effort to provide a literature review on zebrafish models and elucidate their pros and cons to evaluate anti-inflamatory and antioxidant activity.

Abrstract: Bacillus spp. it is a genus that is used to biocontrol post-harvest diseases in various vegetables and fruits during transportation and storage. It suppresses the development of pathogens such as gray mold (Botrytis cinerea) in strawberry cultivation. In this work, the molecular characterization of Bacillus spp. species was carried out. in three cities in Peru: Huaura, Chanchamayo and Cañete. The samples were collected from rhizospheric soil from crop areas, subsequently processed for microbiological isolation, molecular analysis using the 16S rRNA gene and bioinformatic analysis. In total, 14 strains were obtained where they were identified with a minimum of 92.05% and a maximum of 100% similarity: 8 strains of Bacillus subtilis, 4 strains of Bacillus licheniformis, 1 strain of Bacillus paralicheniformis and 1 strain of Bacillus cereus, all the strains were related by constructing a phylogenetic tree.

Cyanobacteria, microorganisms performing oxygenic photosynthesis, must adapt their metabolic processes to environmental challenges such as day and night changes. PipX, a unique regulatory protein from cyanobacteria provides a mechanistic link between signalling protein PII, a widely conserved (in bacteria and plants) transducer of carbon/nitrogen/energy richness, and the transcriptional regulator NtcA, which controls a large regulon involved in nitrogen assimilation. PipX is also involved in translational regulation by interaction with the ribosome-assembly GTPase EngA. However, increases of the PipX/PII ratio are toxic, presumably by abnormally increased binding of PipX to other partner(s). Here we present mutational and structural analyses of reported PipX-PII and PipX-NtcA complexes, leading to identification of single amino acid changes that decrease or abolish PipX toxicity. Four out of 11 mutations decreasing toxicity did not decrease PipX levels, suggesting that the targeted residues (F12, D23, L36, R54) provide toxicity determinants. In addition, one of those four mutations (D23A) argued against the over-activation of NtcA as the cause of PipX toxicity. Since most mutations at residues contacting PII decreased PipX levels, PipX stability would depend on its ability to bind to PII, a conclusion supported by the light-induced decrease in PipX levels observed in Synechococcus elongatus PCC7942.

Chronic granulomatous disease (CGD) is a primary immunodeficiency caused by a defect in the phagocytic function of the innate immune system owing to mutations in genes encoding the five subunits of the nicotinamide adenine dinucleotide (NADPH) oxidase enzyme complex. This review aimed to provide a comprehensive approach to the pathogens associated with chronic granulomatous disease (CGD) and its management. The topics covered included common pathogens infecting CGD patients, granulomas, and CGD-related infectious diseases, including invasive aspergillosis, Mulch pneumonitis, and liver abscesses. In addition, we also covered the differential diagnosis of CGD and its management. Patients with CGD, often children, have recurrent life-threatening infections and may develop infectious or inflammatory complications. The most common microorganisms observed in the patients with CGD are Staphylococcus aureus, Aspergillus spp, Candida spp, Nocardia spp, Burkholderia spp, Serratia spp, and Salmonella spp. Triple-dose antimicrobial prophylaxis with empiric regimens is recommended. Therefore, therapeutics against this disease must be optimised, considering the lack of curative therapies and the long-term side effects of prophylactic regimens. Consequently, allogeneic haematopoietic stem cell transplantation from a human leukocyte antigen-identical donor has been proven to cure CGD.

Based on surveys of winter roost sites, the eastern migratory population of the monarch butterfly (Danaus plexippus) in North America appears to have declined in the last 20 years and this has prompted the implementation of numerous conservation strategies. However, there is little information on the survivorship of first-generation monarchs in the core area of occupancy in Texas, Oklahoma, and Louisiana where overwinter population recovery begins. The purpose of this study was to determine the survivorship of first-generation eggs to third instars at a site in north Texas and to evaluate host plant arthropods for their effect on survivorship. Survivorship to third instar averaged 13.4% and varied from 11.7% to 15.6% over three years. The host plants harbored 77 arthropod taxa, including 27 predatory taxa. Despite their abundance, neither predator abundance nor predator richness predicted monarch survival. However, host plants upon which monarchs survived often harbored higher numbers of non-predatory arthropod taxa and more individuals of non-predatory taxa. These results suggest that ecological processes may have buffered the effects of predators and improved monarch survival in our study. The creation of diverse functional arthropod communities should be considered for effective monarch conservation, particularly in southern latitudes.

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

The human-readable simplicity with which the CSV format was devised, together with the absence of a standard that strictly defines this format, has allowed the proliferation of several variants in the dialects with which these files are written. The latter has meant that the exchange of information between data management systems, or between countries and regions, requires human intervention during the data mining and cleansing process. This has led to the development of various computational tools that aim to accurately determine the dialects of CSV files, in order to avoid data loss at data loading stage in a given system. However, the dialect detection is a complex problem and current systems have limitations or make assumptions that need to be improved and/or extended. This paper proposes a method for determining CSV file dialects through table uniformity, a statistical approach based on table consistency and records dispersion measurement along with the detection of data type over each field. The new method has a 100\% accuracy on a dataset with 148 CSV files composed of samples coming from a data load testing framework and some others added as verification of the parsing routines. In tests on truly messy data, the proposed solution outperforms the state-of-the-art tool by achieving an improvement of about 10\% in the accuracy with which dialects are detected. Furthermore, the proposed method is accurate enough to determine dialects by reading only ten records, requiring more data to disambiguate those cases where the first records do not contain the necessary information to conclude with a dialect determination.

Nowadays, the research and development of on-chip LiDAR sensors for vehicle collision avoidance is growing very fast. Therefore, the assessment of the reliability in obstacle detection using the information provided by LiDAR sensors has become a key issue to be explored by the scientific community. This paper presents the design and implementation of a self-tuning method in order to maximize the reliability of an Internet-of-Things sensors network and to minimize the number of sensors to localize with the required accuracy obstacles by a detection threshold. In order to achieve this goal, models that predict accuracy (i.e., prediction error) for object localization using data collected by LIDAR sensors are designed and implemented in Webots Automobile 3D simulation tool. The approach is based on combining different techniques. Firstly, point-cloud clustering technique and an error prediction model library composed by a multilayer perceptron neural network with backpropagation, k-nearest neighbors and linear regression are explored. Secondly the above-mentioned techniques for modeling are also combined with a supervised and reinforcement machine learning technique, Q-learning in order to minimize the detection threshold. In addition, a IoT driving assistance simulated scenario with a LiDAR sensor network is designed in order to validate the prediction model and the optimal configuration of the sensor network to guarantee reliability in obstacle localization. The results demonstrate that the self-tuning method is appropriate to increase the reliability of the sensor network whereas minimizing the detection threshold

Non-conventional resonances, both acoustic and photonic, are found in metallic particles with a toroidal nanopropeller geometry that is generated by sweeping a three-lobed 2D-shape along a spiral with twisting angle, α. For both optical and acoustic cases, the spectral location of resonances experiences a red-shift as a function of α. We demonstrate that the optical case can be understood as a natural evolution of resonances as the spiral length of the toroidal nanopropeller increases with α, implying a huge helicity dependent absorption cross section. In the case of acoustic response, two red-shifting breathing modes are identified. Additionally, even a small α allows the appearance of new low-frequency resonances, whose spectral dispersion depends on a competition between length of the generative spiral and the pitch of the toroidal nanopropeller.

A Q-switched Nd:YAG laser was focused on Pb-Ti alloy samples in several Laser Induced Breakdown experiments in order to measure the Stark parameters of several spectral lines (58) of single ionized Titanium including the 3504.89 Å, and the 3510.83 Ålines (where we aported new experimental and theoretical values).Diagnostics of the laser induced plasmas (electron density and electron temperature) was performed using Balmer’s H alpha line (6562.7 Å).Temperatures were obtained by the Boltzmann Plot technique with spectral lines of Pb I (after correction for its evident self-absorption).Subsequently, calculations by the Griem approach of the Stark broadening parameters for several spectral lines were performed using the Gaunt factors proposed by Van Regemorter and those proposed by Douglas H. Sampson. In the latter cases the values obtained were very close to the experimental values. It allows us to assume that the calculations made for the spectral lines of Ti II, without experimental information, are more accurate using the Gaunt factors proposed by Sampson.

Hazelnut (Corylus avellana L.) is of great agroeconomic importance, prized for its nutritional value and antioxidant properties. Its yield and quality may differ due to factors such as season (S), locality (L) and cultivar (C). Our objective was to determine the dynamics of morphological features and antioxidant properties in nuts of Barcelona and Tonda di Giffoni (TDG) cultivars planted at two localities (Cunco and Perquenco) during three productive seasons (S1, S2 and S3). Barcelona grown in Perquenco in S1 and S3 (less precipitation, more solar radiation), performed better than in Cunco with respect to most morphological nut, kernel and shell features, and the same parameters generally had the same trends for TDG in S2 and S3. Among the seasons at the same localities, the differences between the predominant condition defects for both cultivars were in the decreasing order wrinkled/deformed kernels, double kernels, blank and mold ker-nels, with about 75% of hazelnuts without defect. In both cultivars, the shell had higher antioxi-dant properties that increased in S1 and S3 at both localities, and were consistently higher than in the kernels. Lipid peroxidation was higher in the kernel than shell in both cultivars and local-ities for S1 and S3. The results of this study suggest that the different hazelnut cultivar features including physical and chemical components depend on season and locality, which offers im-portant clues for all those interested in the hazelnut industry.

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.

Clinical training in medical schools in Spain is performed by rotations in university hospitals. During these internships, students are expected to acquire and master basic procedural skills. However, the assessment tools available rarely check whether these skills are completely acquired by the students. We have used an e-portfolio to determine the optimal number of times the students need to repeat a procedure to be able to perform it independently. The results were compared with the actual performance during the internships. An e-portfolio collected qualitative information about the internships. Quantitative information was also requested about the number of times each clinical skill was performed. Later, a survey asked these students and their teachers the optimal number of times each skill should be repeated before it could be considered fully acquired. The questionnaire was answered by 98.6% of the students and 70.3% of their teachers. Out of the 21 clinical skills and procedures selected, both students and their tutors agreed in a similar optimal value in 16 of them; only in five of them, teachers thought that students needed a greater number of times than that selected by the students. When these optimal values were compared with the actual values recorded in the portfolio during the internships, it was found that about half of the clinical skills were carried out less frequently than expected, thus providing an important feedback about the internships. Quantitative information collected in portfolios reveals a moderate mismatch between students and tutors perceptions of their training needs.

The optimized design of catalyst layer (CL) plays a vital role to improve the performance of polymer electrolyte membrane fuel cells (PEMFCs). The need to improve transport and catalyst activity is especially important at low Pt loading, where local oxygen and ionic transport resistances decrease the performance due to an inevitable reduction of active catalyst sites. In this work, local oxygen and ionic transport are analyzed using direct numerical simulation on virtually reconstructed microstructures. Four morphologies are examined: (i) heterogeneous, (ii) uniform, (iii) uniform vertically-aligned, and (iv) meso-porous ionomer distributions. The results show that the local oxygen transport resistance can be significantly reduced, while maintaining good ionic conductivity, through the design of high porosity CLs (ε≃0.6−0.7) with low agglomerated ionomer morphologies. Ionomer coalescence into thick films can be effectively mitigated by increasing the uniformity of thin films and reducing the tortuosity of ionomer distribution (e.g., good ionomer interconnection in supports with a vertical arrangement). The local oxygen resistance can be further decreased by the use of blended ionomers with enhanced oxygen permeability and meso-porous ionomers with oxygen transport routes in both water and ionomer. In summary, achieving high performance at low Pt loading in next-generation CLs must be accomplished through a combination of high porosity, uniform and low tortuosity ionomer distribution, and oxygen transport through activated water.

Seeds from several Ribes taxa were surveyed for phenolic compounds and in vitro antiproliferative activity against HT-29 colorectal cancer cells. Total phenolic compounds were analysed through the Folin-Ciocalteu procedure, while phenolic profiles were analysed by LC coupled to a single mass spectrometer Orbitrap using an electrospray interface (ESI). Antitumor effects were established using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Total phenolics ranged from 11.4 in R. alpinum to 94.8 mg of caffeic acid equivalents (CAE)/g in R. nigrum 'Koksa'. Concerning phenolic compounds, four were hydroxylated benzoic acids, four cinnamic acid derivatives, eight flavonoids, and nine flavonoid glycosides. The growth inhibition against HT-29 cancer cells was exercised much better by R. nigrum 'Koksa' and Ribes 'Erkeeni' (GI50 37 and 42 µg/ml). All Ribes extracts, except R. nigrum 'Hara katarlik', showed higher activity than that of R. rubrum (GI50 at 72 h: 99 µg/ml). Interestingly, the highly bioactive extract from Ribes 'Erkeeni' contains all detected phenolics, while R. nigrum 'Koksa' lacks only populnin. Therefore, the high bioactivity found for such extracts could be due to a synergy due to all detected compounds. This work constitutes a comprehensive action for expanding knowledge on the phenolic profiles and antitumor activity of GLA-rich Ribes seeds.

The use of clays in beauty care comes from ancient times, with therapeutic use since prehistory, and it is considerably relevant in the current cosmetic industry worldwide. In our review, we described types of clay and clay minerals used in cosmetics and dermocosmetics, compositions, usages as active compounds and excipients, and observations about formulation techniques. From this research, we could notice that although many scientific and specialized literature reported the characterization of clays, only some involving efficacy tests when incorporated into cosmetic products, mainly concerning haircare applications. By the exposed, our review could be considered and encouraged in the coming years to provide scientific and technical information for the cosmetic industry regarding the multifunctional use of clays and clay minerals.

(1)Aims of the study: calculating the underreporting ratio for two different medications, a fixed combination of 0.5% timolol + 0.2% brimonidine + 2.0% dorzolamide (antiglaucoma) and a fixed combination of sodium hyaluronate 0.1% + chondroitin sulfate 0.18% (artificial tear) and characterizing the features influencing the reporting of adverse drug reactions (ADRs) in spontaneous reporting; (2) Methods: the underreporting ratio was calculated by comparing the adverse drug reactions reported in the spontaneous reporting database for every 10,000 defined daily doses marketed and the adverse drug reactions from an active surveillance study for every 10,000 defined daily doses used for different drugs (antiglaucoma and artificial tear). The factors related to the report in spontaneous reporting through statistical tests were also determined; (3) Results: The underreporting ratio of spontaneous reporting was 0.006029% for antiglaucoma and 0.003552% for artificial tear; additionally, statistically significant differences were found for severity, unexpected adverse drug reactions, and incidence of adverse drug reactions in females; (4) Conclusions: The underreporting ratio of ADRs related to ophthalmic medications indicates worry since the cornerstone of pharmacovigilance focuses on spontaneous reporting. Besides, since underreporting seems to be selective, the role of certain aspects like gender, seriousness, severity, and unexpected ADRs, must be considered in future research.

Amyotrophic Lateral Sclerosis (ALS) is an irreversible neurodegenerative disease with no known cure. Recent studies suggest a strong metabolic component in ALS pathogenesis and have shown an inverse relationship between leptin levels and ALS progression, although the effects of leptin as a treatment have not yet been studied. Therefore, we aim to examine whether the acute treatment with leptin has beneficial effects on brain pathology and cognitive function in the transgenic TDP43A315T line of ALS. Mice were treated intranasally (IN) with 0.03mg/kg of leptin or vehicle (VH) daily for 7 days. Data showed a progressive decline in body weight and motor coordination in TDP43A315T mice. Moreover, Lep-treated TDP43A315T mice showed an earlier disease onset, along with an improvement in motor performance. Altered levels of some of the adipokines and metabolic proteins studied were found in TDP43A315T mice, which were differently expressed among Lep-treated and VH-treated animals. Furthermore, some correlations were found among the serum levels of this proteins in WT and TDP43A315T mice. As far as we know, this is the first pilot study to provide evidence of the therapeutic effect of leptin treatment in a mice model of ALS, although further studies are needed to expound on the underlying mechanisms.

Objectives: To analyse and detail surgical process improvement activities that achieve the highest economic impact. Methods: Over 4 years, a team of technicians and healthcare professionals implemented a set of Lean surgical process improvement projects at Vall d’Hebron University Hospital (VHUH), Barcelona, Spain. These projects now form part of the daily routine in the surgical process. The economic impact on the hospital's surgical activity budget was analysed. Results: Process improvements have led to annual operational savings of over € 8.5 million. These improvements include better patient flow, better management of information between healthcare professionals, and improved logistic circuits. Conclusions: The current cultural shift towards process management in large hospitals implies shifting towards results-based healthcare, patient-perceived value (VBHC) and value-added payment. A Lean project implementation process requires long-term stability. The reason a considerable number of projects fail to complete process improvement projects is the difficulty involved in establishing the project and improving management routines. Few studies in the literature have investigated the economic impact of implementing Lean management a posteriori, and even fewer have examined actual cases. In this real case study, changes to surgical block management were initiated from zero. After being carefully thought through and designed, changes were carried out and subsequently analysed.

Collision avoidance is an important feature in advanced driver-assistance systems, aiming at providing correct, timely and reliable warnings before an imminent collision (objects, vehicles, pedestrians, etc.). A co-simulation framework is proposed in this paper to address the design and evaluation of collision avoidances in a cyber-physical system. The co-simulation framework is supported on the interaction between SCANeR and Matlab/Simulink. From the best of authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip LIDAR sensors in a cyber-physical system (CPS) considering traffic scenarios is presented. The CPS is designed and implemented in SCANeR. Secondly, an obstacle recognition library with three specific Artificial Intelligence-based methods is also designed based on sensory information database provided by SCANeR. Three methods for collision avoidance detection are considered, i.e.; a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods for detecting obstacles before different weather conditions is done with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and fog conditions, the support vector machine in rainy and self-organized map in snowy conditions.

Purpose: Young transgender and non-binary are exposed to situations of discrimination and have a greater risk of violence. The purpose of this study is to analyze which protective, violence and health and well-being factors have more influence on transgender and non-binary people compared to cisgender people. Method: The sample comprised 856 people between 14 and 25 years old. A survey including questions about sociodemographic information and protective, violence and health and well-being factors was designed ad hoc for this study. Results: The results show non-binary group received the least support from family and friends, higher risk of suffering cyberbullying and a higher feel isolated and unhappy. Non-binary and transgender have suffered more verbal attacks both inside and outside their school and physical attacks at school than cisgender young. Conclusions: These results are important and may contribute to promote public policies and clinical interventions to favor the integration of non-binary and transgender people in our society.

Irregular female migration to Europe is a growing phenomenon, as more and more women are fleeing their countries of origin due to gender inequality and violence. During the migration process, women experience physical, psychological and social problems that affect their sex lives. The aim of our study is to describe and understand how irregular migrant wom-en living in humanitarian reception centers experience their sexuality at different stages of the migration process. This qualitative phenomenological study collected data through a sixteen in-depth interviews with irregular migrant women between January and February 2023. Data anal-ysis was carried out using ATLAS-ti 23.0 software, from which three themes were extracted: 1) The sexual reality of sub-Saharan women, 2) In search of a better life: take the risk or surrender, and 3) The migrant sexual revolution. The sexual reality of sub-Saharan women is subject to a complex normative order. The migratory process has severe consequences on migrant women's sex life. The sexual needs of irregular migrant women admitted to humanitarian reception cen-ters undergo a process of change that must be understood by healthcare providers in order to make improvements to care provision.

Background. The treatment for patients with high-grade gliomas includes radiation therapy and temozolomide. However, some patients do not respond to temozolomide because they have a methylation reversal mechanism through the enzyme O6-methylguanine-DNA-methyltransferase. This biomarker has been used as a prognostic factor in patients receiving treatment with temozolomide. However, not all patients respond in the same way, which suggests the existence of other genes involved in resistance to temozolomide. Materials and Methods. A group of 31 patients with high-grade gliomas was recruited and were clinically, image pattern, and pathologically characterized. The sequencing of 324 genes related to different types of cancer was performed to detect mutations. Subsequently, a statistical analysis was conducted to determine the mutated genes that were most related to resistance to treatment. Results. The genes related to the second relapse of patients with high-grade glioma after the use of temozolomide according to Stupp protocol and metronomic dose were PIK3C2B, KIT, ERBB3, and MLH1. Conclusions. Considering the results obtained, we suggest that the mutations in the four genes and the methylation of the gene promoter that codes for MGMT protein could be related to the clinical evolution of patients with high-grade gliomas and its response to treatment with temozolomide.

Abstract: Background: In contrast to conventional definitions, the contemporary conceptualization of adulthood emphasizes psychological characteristics over sociodemographic milestones. Concurrently, there is a growing proposition that individuals' perceptions of adulthood exert a substantial influence on the mental well-being of adolescents and adults. However, empirical examination of this hypothesis has been notably limited to date. Method: This study applied some adulthood markers, and multiple mental health indices (including Well-being, Optimism, Alexithymia, Satisfaction with life, Goldberg's index of mental health, Dark triad, and dimensional personality disorders) to a community sample comprising 1772 individuals in Spain, spanning ages from 16 to 93 years. Results: The findings support the overarching hypothesis, as perceptions of adulthood exhibit significant associations with almost all measured mental health indices, especially with those conforming a factor of Negative emotions. These associations persist even after accounting for age and socioeconomic status, and in alignment with the psychological paradigm of adulthood, they demonstrate stability across different age cohorts. Conclusions: The study establishes that such perceptions of adulthood represent a modifiable factor contributing to positive mental health. The implications of these findings for the formulation of public policies aimed at promoting mental health in the context of adulthood are deliberated, as well as a number of future studies.

The growing increase in infections caused by C. tropicalis, associated with its drug resistance and consequent high mortality, especially in immunosuppressed people, today generates a serious global public health problem. In the search for new potential drug candidates that can be used as treatments or adjuvants in the control of infections by these pathogenic yeasts, the objective of this research was to evaluate the action of isoespintanol (ISO) against the formation of biofilms fungal, the mitochondrial membrane potential (∆Ψm) and its effect on the integrity of the cell wall. We report the ability of ISO to inhibit the formation of biofilms by up to 89.35%, in all cases higher than the values expressed by amphotericin B (AFB). Flow cytometric experiments using rhodamine 123 (Rh123) showed the ability of ISO to cause mitochondrial dysfunction in these cells. Likewise, experiments using calcofluor white (CFW) and analyzed by flow cytometry, showed the ability of ISO to affect the integrity of the cell wall by stimulating chitin synthesis; these changes in the integrity of the wall were also observed through transmission electron microscopy (TEM). These mechanisms are involved in the antifungal action of this monoterpene.

This study determines the equivalent stress intensity factor (SIF) model that best fits the experimental behavior of low-carbon steel under mixed mode (I and II). The study assessed Tanaka, Richard, and Pook's equivalent SIF models. The theoretical values used for comparison correspond to experimental results in a modified C(T) geometry by machining a hole ahead of the crack tip subjected to fatigue loads with a load ratio of R = 0.1. The comparison involved the SIF for six experimental points and the values computed through the numerical simulation. The Paris, Klesnil, and modified Forman-Newman crack growth models were used with each equivalent SIF to analyze the prediction in the estimated number of cycles. The Klesnil model showed the closest prediction since the error between the calculated and experimentally recorded number of cycles is the lowest. However, the material behavior reflects a reduced crack propagation rate attributed to plasticity in the crack tip. Results suggest that Asaro equivalent SIF conservatively estimates the element lifespan with increasing errors from 2.3% at the start of growth to 27 % at the end of the calculation.

In recent years, the use of long-term seismic monitoring systems for the protection of structures is becoming increasingly widespread. This is because more and more awareness is gradually developing regarding the importance of keeping structures under observation so as to prevent any damage scenarios. Within the field of Structural Health Monitoring, data driven techniques allow to process and analyze data collected on site. This paper presents a Mode Tracking procedure to obtain the time-histories of the natural frequencies of a monumental structure. The procedure is applied on the Sanctuary of Vicoforte, an important monumental structure site in Piedmont known for its imposing oval dome and characterized by a permanent structural monitoring system. Through the procedure presented in the paper it has been possible to obtain and observe the time series of the first natural frequencies of the structure considering various aspects, including the temperature variation.

Among the plant resources in pre-Columbian Mexico and Central America, the Chia (Salvia hispanica L.) is unique in being the only member of the Lamiaceae cultivated for the mericarps. Recently the crop has gained considerable attention due to its high of content omega-3 polyunsaturated fatty acid, antioxidants, fibre and protein classifying it as a nutraceutical.

The cultural and historical heritage of a city is a major resource to attract tourists. Therefore, reaching out to perceive and identify the characteristics of persons visiting a locality attracted by their property is relevant for the purpose of better meeting their expectations and needs. This research focuses on knowing the perceptions, motivations and satisfaction of women visiting Cordoba (Spain). Thus, on the basis of the questionnaire carried out on women visiting Cordoba during the months of June and November 2019, a statistical analysis has been made. Using various multivalent case-grouping techniques, tourist segments with similar perceptions of cultural heritage have been detected. Moreover, non-parametric statistical techniques have showed up significant differences between the valuations obtained in the various segments. This analysis has exposed a segment of women who, known as absorbent tourists, are characterized by the high cultural motivation to visit the city of Cordoba linked to the heritage they have visited. The conclusions obtained should be useful in adjusting the city's tourist supply to the specific demand of a population sector such as women visiting the city.

Considerable amounts of agro-industrial by-products are discarded or burnt as fuel every year. However, they can be utilized as a valuable source of fiber, phenolics and other useful compounds such as antioxidants. The profile of beneficial compounds can be affected by genotype, locality, orchard management and productive season, adding or decreasing the bioactive potential of by-products. In this study, hazelnut (Corylus avellana L.) and walnut (Juglans regia L.) nutshells were investigated for their fiber content and antioxidant capacity as valorized by-products for the industry. Determinations (ORAC, TPC and color asses) were performed in hazelnut and walnut orchards located in Southern Chile during three consecutive seasons (2020/21; 2021/22 and 2022/23). Analyses of oxygen radical absorbance capacity (ORAC) in nutshells showed the highest ORAC from both species in the season 2020/21 (3217 µmol TE g1DW for hazelnut shells and 4663 µmol TE g DW1 for walnut shells), while variability in the consecutive seasons was lower for hazelnut than in walnut. Total phenolic content in hazelnut shells was positively correlated with L* (R: 0.883) and E (R: 0.924) during 2020/21 season, also with L* for 2022/23 (R: 0.907). While ORAC was negatively correlated with L* (R: 0.922) in 2021/22. In addition, morphological and structural features of both nutshells examined by Scavenging Electron Microscopy (VP-SEM) and Confocal Scavenging Laser Microscopy (CSLM) revealed differential tissue distribution and accumulation patterns of both cellulose and lignin. On the other hand, photo-colorimetric values were determined for both shells and corresponding seasons, and non-significative differences were found both shells and among seasons Finally, these results provide insight into the physicochemical characteristics of two shell types which should be considered together with antioxidant capacity in their valorization as a residual material.

The aim of this research work is to get a method for Galfenol electrodeposition thought which we can control the desired percentage of Ga versus Fe that has the maximum magnetostriction constant. Galfenol is electrodeposited on an optical fiber with an imbedded Fiber Bragg Grating (FBG) in its core. The final objective, that goes further of the scope of this research, is to get an optical magnetostrictive sensor. The device will sense magnetic field or current based on the combination of this magnetostrictive Galfenol, that will stress the optical fiber with the application of magnetic field or current and will change the reflected wavelength of the FBG as a consequence of the variation of the Bragg wavelength. We have developed a method of electrodeposition that allows controlling the density of current in the electrodeposition process in order to get the desired percentage of Ga and Fe in the alloy Ga X Fe 1-x. We have manufactured a set of samples with different parameters (as density of current and pH) and we have characterized these samples morphological, structural and magnetically. With this research we want to give to the scientific community the groundwork to design magnetostrictive optical sensors based on and FBG coated by giant magnetostrictive material. In this paper we have developed a method of covering the optical fiber controlling the composition of (Ga X Fe 1-X) in order to be able to get the maximum magnetostriction constant.

Aim: In the present work we have studied the role of platelets and microvesicles in patients with severe hemophilia A (HA) treated under the regimen of prophylaxis. We have analyzed whether the administration of coagulation factor FVIII modifies this hemorrhagic phenotype in a cohort of 16 patients with diagnosis of severe HA, who were on prophylactic treatment with recombinant FVIII. Methods: Blood tests were performed before (72h without FVIII, baseline sample) and after 15 minutes of FVIII infusion. As a control group, 15 healthy subjects were studied. Platelet aggregation was determined by closure time, optical aggregation, impedance aggregation and flow cytometry. We also studied the expression of the platelet activation markers P-selectin, CD63, platelet-tissue factor, formation of platelet-leukocyte aggregates and tissue factor exposure. The total number of platelet and endothelial microvesicles were also analyzed by flow cytometry, as well as platelet cytosolic Ca²⁺ mobilization. Results: We found no significant differences in platelet function in patients with severe HA in prophylactic treatment before and after FVIII infusion. After FVIII administration, patients presented fewer endothelial microvesicles, indicating that the treatment does not increase one of the possible thrombotic risk markers of these patients. The total amount of plasma microvesicles and the platelet microvesicles were decreased in patients with HA compared to the control group. Conclusions: Our results do not support any effect of FVIII on platelet function in patients with severe HA treated under the regime of prophylaxis.

The influence of hafnium metal (Hf) and sulfate ions (SO₄^-2) on the acidic properties of SiO₂ mesopores synthesized by a non-hydrothermal method was studied using the following characterization techniques; TG-DTG, XRD, BET, SEM, TEM, EDS, FTIR, n-butylamine titration, FTIR-pyridine, and alcohol dehydration. The incorporation of 3.6% mol of Hf during the silicate synthesis step caused the characteristic structural arrangement of MCM-41 to collapse. However, an increase in the acid strength of the catalyst of up to 315 mV was observed, with Brönsted and Lewis-type acid sites being mostly present therein. Furthermore, the acidity of Hf- and (SO₄^-2) -modified SiO₂ in the dehydration of ethanol and methanol was evaluated, resulting in a selectivity towards ethylene and dimethyl ether, respectively. Acid solids have enormous potential to produce important compounds for the chemical industry using alternative routes other than petrochemical processes. They also represent a significant advance for biorefineries.

Overweight and Obesity are global health and economic concerns. According to the World Health Organization, the number of individuals with obesity has nearly tripled since 1975. This health issue is currently considered an epidemic, affecting over 1.9 billion adults and 340 million children and adolescents. It contributes to more than 5 million deaths each year and has a global economic burden that will reach $4.32 trillion annually by 2035, according to the World Obesity Federation. This disease can affect every system of the human body and can lead to complications such as metabolic syndrome, diabetes, cancer, dyslipidemia, cardiovascular diseases, and hypertension, among others. Treatment may sometimes include diet, exercise, drugs, and bariatric surgery. Nonetheless, not all people have access to these treatments, and public health strategies consider prevention the most important factor. In this regard, recent investigations are aiming to find alternatives and adjuvants for the treatment of obesity, its prevention, and the reversion of some of its complications, using natural sources of anti-obesogenic compounds like polyphenols, terpenes, alkaloids, saponins, among others. In this review, we gather the most current information using PubMed, Google Scholar, Scopus, Cochrane, and Web of Science. We present and discuss the current information about natural products that have shown anti-obesogenic effects at a molecular level. We also consider the impact of dietary habits and lifestyle in preventing overweight and obesity due to the evidence of the benefits of certain foods and compounds consumed regularly. We discuss mechanisms, pathways, and receptors involved in the modulation of obesity, especially those related to inflammation and oxidative stress linked to this disease, due to the relevance of these two aspects in developing complications.