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Abstract The adverse outcome pathway (AOP) concept has gained attention as a way to explore the mechanism of chemical toxicity. In this study, quantitative structure–activity relationship (QSAR) models were developed to predict compound activity toward protein targets relevant to molecular initiating events (MIE) upstream of organ-specific toxicities, namely liver steatosis, cholestasis, nephrotoxicity, neural tube closure defects, and cognitive functional defects. Utilizing bioactivity data from the ChEMBL 33 database, various machine learning algorithms, chemical features and methods to assess prediction reliability were compared and applied to develop robust models to predict compound activity. The results demonstrate high predictive performance across multiple targets, with balanced accuracy exceeding 0.80 for the majority of models. Furthermore, stability checks confirmed the consistency of predictive performance across multiple training-test splits. The results obtained by using QSAR predictions to identify known markers of adversities highlighted the utility of the models for risk assessment and for prioritizing compounds for further experimental evaluation. Scientific contribution The work describes the development of QSAR models as tools for screening chemicals with potential systemic toxicity, thus contributing to resource savings and providing indications for further better-targeted testing. This study provides advances in the field of computational modeling of MIEs and information from AOP which is still relatively young and unexplored. The comprehensive modeling procedure is highly generalizable, and offers a robust framework for predicting a wide range of toxicological endpoints.

Background: Until recently, the affective components of education had long been undervalued. Today, one finds ever more studies on cognitive and affective interrelationships that are lending support to the idea that affect and cognition are best understood when viewed as independent and complementary mental functions. Purpose: The present work analyses the emotions of prospective secondary education teachers, distinguishing them by gender, in relation to the teaching of Biology, Geology, Physics and Chemistry in order to contribute to designing subsequent interventions targeted at improving science teachers' occupational health. Sample: The total sample consisted of 178 students (53 male and 125 female) of the post-graduate teaching certificate course at the University of Extremadura, all of whom were prospective secondary school teachers. We also worked with a sub-sample of 66 Science and Engineering graduates (33 male and 33 female). Design and Methods: A questionnaire was prepared that includes items on each of the emotions that the prospective teacher might feel when teaching the science content of the proposed courses. The chi-squared test was used to determine whether a relationship exists between emotions and the variable gender when it came to their teaching Biology, Geology, Physics and Chemistry at the compulsory secondary education level. Results: The results showed that the male teachers more frequently report positive emotions than the female. The latter manifested an increase in negative emotions in teaching Geology, Physics and Chemistry content. And the study of the sub-sample showed positive emotions are more frequently reported than negative ones in all four subjects, with this being particularly so in Biology. Conclusions: The study of emotions is vital in the educational formation of prospective secondary teachers. These students will soon face day-to-day life in the classroom, and many of them, especially the women, declare themselves to be emotionally vulnerable, since they describe themselves as experiencing stronger negative emotions. It is essential to provide prospective secondary teachers with a program of support and monitoring during their teaching practice so as to foster awareness of their emotions towards science and its learning. The aim must be to enhance their capacity for self-regulation and control to change those emotions, and to consolidate healthy habits.

8-Hydroxyquinoline and its derivatives are compounds with a variety of applications in various fields of knowledge such as medicine, biological sciences, and chemistry. Many of these applications are possible because 8-hydroxyquinoline forms stable and insoluble metal chelates with a range of metals such as copper, cobalt, calcium, iron, and nickel. One of the possible applications of 8-HQ chelates is the production of metal oxides by thermal decomposition, however, there are few studies in the literature using quinolinates for this purpose. If the chelates are synthesized simultaneously, it is possible to obtain double oxides such as cobalt ferrite, which has numerous applications due to its magnetic properties. In this way, the present work aims to the simultaneous synthesis of cobalt II and iron III quinolinates at different pH values, as well as their characterization by XDR, SEM, TEM, FTIR and Raman analysis. Finally, the quinollinate synthetized were applied as precursors to obtain cobalt ferrite by thermal decomposition.

This article develops a general thermodynamic treatment to predict the direction of shift in a chemical equilibrium when it is subjected to a stress. This treatment gives an inequality that relates the change in the perturbed variable and the change that the equilibrium shift produces in the conjugated variable. To illustrate the generality of this approach, it has been applied to predict the direction of shift caused by changes of pressure, volume, and amount of substance. In this last case, the well-known unexpected shift in the ammonia synthesis equilibrium upon addition of nitrogen is easily explained. From the above referred inequality and the stability criteria of thermodynamics some conclusions have been obtained about the direction of shift in terms of extensive and extensive variables. This article is suitable for physical chemistry courses. (Contains 1 table, 3 figures, and 5 notes.)

In the present article, the scientific journey that led to the development of the Nernst equation, a cornerstone in modern electrochemistry, is discussed. The paper not only explores historical achievements but also traces the evolution of scientific ideas and highlights the key figures who laid the conceptual and experimental groundwork for the seminal contributions of Nernst to the understanding of electrochemical systems. In this exploration, particular attention is paid to the examination of the first three articles published by Nernst between 1888 and 1889. These essential works marked the inception of the engagement of Nernst with the Leipzig Physical Chemistry circle, comprising the distinguished quartet: van’t Hoff, Arrhenius, Ostwald, and Nernst himself. Furthermore, the present study examines the intricate relationship between the Nernst equation and the four basic laws of Thermodynamics, all in an approach accessible to undergraduate students. A concise review elucidates the interpretation and significance of these foundational thermodynamic principles and explain how they hold the formulation of the Nernst equation.

The aim of this study was to analyze the effects of different exercise interventions involving chronic exercise (endurance and strength groups) carried out in physical education on physical fitness and cognitive functions. A group of 72 adolescent students from the city of Melilla (Spain) aged between 13 and 17 years old (M = 15.38, SD = 0.78) participated in the current study. A D2 attention test was used in order to analyze selective attention and concentration. Physical fitness was measured through the ALPHA-Fitness battery. The analysis taken indicated a significant relationship between physical fitness level, attention and concentration. Moreover, the intervention resulted in significant reductions in body weight and waist circumference in the resistance and strength groups compared to the control group, indicating positive effects on body composition. All the groups demonstrated enhanced aerobic capacity, as evidenced by improvements in VO2 max after the intervention period. Furthermore, significant enhancements in most attentional measures (TR, TA, O, C, TOT, CON and TR−) were observed across all the groups, with an additional temporary improvement in TR+ for the strength group. Our findings suggest that an 8-week school-based exercise intervention, regardless of specific exercise type (resistance or strength), can positively impact body composition, aerobic capacity and attention in adolescents. These results emphasize the importance of integrating physical activity programs into school environments to promote holistic health and well-being in this population. Future research should focus on elucidating the underlying mechanisms of these effects and exploring the long-term benefits of such interventions.

This paper explores the relationships between m-learning, learning outcomes, and developing critical thinking in university students. A systematic review of empirical articles in English published in journals indexed in the Web of Science from 2015–May 2024 was carried out. A sample of 50 articles was obtained. The results show that, in most of the analyzed articles, integrating m-learning tools can potentially to improve students’ learning outcomes and critical thinking skills. Considering the above, we recommended that educators and university managers integrate and promote the adoption of new technologies in teaching methods. Several recommendations are provided for the effective integration of m-learning into learning activities, stressing the importance of teachers becoming familiar with technology-enhanced learning environments early in their training.

This study investigates the electro-osmotic flow of a biological fluid (blood with varying cholesterol levels) in annular flow to simulate a first approximation to arterial occlusion. The fluid´s rheology is characterized by a multi-modal convected Maxwell model equation. The charge density follows the Boltzmann distribution, governing the electrical field. Mathematically, this scenario can be modeled by the Poisson–Boltzmann partial differential equation. Assuming a small zeta potential (less than 25 mV) using the Debye–Huckel approximation and considering a pulsatile electrical field, analytical solutions are derived using the Fourier transform formalism. These solutions, expressed in terms of the modified Bessel function, provide transfer functions for axial velocity and volumetric flow as functions of material parameters represented by characteristic dimensionless numbers. This study further analyzes thermal, electric, inertial, viscoelastic, and various interactions within the plasma, hematocrit, hematocrit–cholesterol, and cholesterol–cholesterol as well as weight concentration through numerical simulations. Finally, the flow and rheology predictions are validated using experimental data on human blood with varying cholesterol levels. The obtained transfer functions reveal that the electric–thermal–viscoelastic effects and the multiple geometric relationships contribute to the dynamic response of the interactions between the input electrical field and output volumetric flow and shear stress functions, leading to and evolution of resonance curves. It is noteworthy that electro-osmotic flow in blood with pathologies associated with low and high cholesterol has been scarcely reported in the literature on rheology. Thus, this work represents a significant contribution to the field.

Abstract This mini–review summarises examples of photo and photoelectrochemical CO2 reduction reactions (CO2RR) using semiconductor–molecular catalyst–based hybrid assemblies in which studies of charge transfer dynamics were also performed. In these catalysts, the grand challenges are controlling ultra–fast one–electron charge separation and simultaneously governing its impact on the efficiency and product selectivity in the multielectron and multi–proton–assisted CO2RR. In practice, several unwanted electron recombination processes occur in the femtosecond to millisecond timescale range impacting the overall catalysis efficiency. Titanium di‐oxide (TiO2) nanoparticle, mesoporous TiO2 film, copper indium sulphide (CuInS2) quantum dots were used as semiconductor materials, in turn rhenium (I) bipyridine, cobalt (II) terpyridine, cobaloxamine complex, and iron (III) porphyrins were investigated as molecular catalysts. The results of the charge transfer dynamic studies operating in such hybrid systems shed light on their charge accumulation processes, their rate constants for the intramolecular charge transfer processes and the decay lifetimes of the different excited state species that are produced. Moreover, a comprehensive understanding of the catalysts’ charge transfer dynamics is crucial to identifying detrimental charge recombination pathways. These undesired pathways can be used as rational basis for improving the design of future multi–redox–driven hybrid catalysts.

In the context of the internet of things, and particularly within distributed measurement systems that are subject to high privacy risks, it is essential to emphasize the need for increasingly effective privacy protections. The idea presented in this work involves managing critical traffic through an architectural proposal aimed at solving the problem of communications between nodes by optimizing both the confidentiality to be guaranteed to the payload and the transmission speed. Specifically, data such as a typical sensor on/off signal could be sent via a standard encrypted channel, while a sensitive aggregate could be transmitted through a dedicated private channel. Additionally, this work emphasizes the critical importance of optimizing message sizes to 5 k-bytes (small payload messages) for transmission over the reserve channel, enhancing both privacy and system responsiveness, a mandatory requirement in distributed measurement systems. By focusing on small, encrypted payloads, the study facilitates secure, timely updates and summaries of network conditions, maintaining the integrity and privacy of communications in even the most challenging and privacy-sensitive environments. This study provides a comprehensive performance analysis of IoT networks using Dark Net technologies and MQTT protocols, with a focus on privacy and anonymity. It highlights the trade-offs between enhanced security and performance, noting increased latency, reduced bandwidth, and network instability when using TOR, particularly with cipher suites like AES256-GCM-SHA384 and DHE-RSA-CHACHA20-POLY1305. The research emphasizes the need for further exploration of alternative protocols like LWM2M in secure IoT environments and calls for optimization to balance privacy with performance in Dark-Net-based IoT deployments.

The imminent depletion of oil resources and increasing environmental pollution have driven the use of clean energy, particularly wind energy. However, wind turbines (WTs) face significant challenges, such as critical component failures, which can cause unexpected shutdowns and affect energy production. To address this challenge, we analyzed the Supervisory Control and Data Acquisition (SCADA) data to identify significant differences between the relationship of variables based on data reconstruction errors between actual and predicted values. This study proposes a hybrid short- and long-term memory autoencoder model with multihead self-attention (LSTM-MA-AE) for WT converter fault detection. The proposed model identifies anomalies in the data by comparing the reconstruction errors of the variables involved. However, more is needed. To address this model limitation, we developed a fault prediction system that employs an adaptive threshold with an Exponentially Weighted Moving Average (EWMA) and a fixed threshold. This system analyzes the anomalies of several variables and generates fault warnings in advance time. Thus, we propose an outlier detection method through data preprocessing and unsupervised learning, using SCADA data collected from a wind farm located in complex terrain, including real faults in the converter. The LSTM-MA-AE is shown to be able to predict the converter failure 3.3 months in advance, and with an F1 greater than 90% in the tests performed. The results provide evidence of the potential of the proposed model to improve converter fault diagnosis with SCADA data in complex environments, highlighting its ability to increase the reliability and efficiency of WTs.

Computer vision has advanced much in recent years. Several tasks, such as image recognition, classification, or image restoration, are regularly solved with applications using artificial intelligence techniques. Image restoration comprises different use cases such as style transferring, improvement of quality resolution, or completing missing parts. The latter is also known as image inpainting, virtual image inpainting in this case, which consists of reconstructing missing regions or elements. This paper explores how to evaluate the performance of a deep learning method to do virtual image inpainting to reconstruct missing architectonical elements in images of ruined Greek temples to measure the performance of different activation functions. Unlike a previous study related to this work, a direct reconstruction process without segmented images was used. Then, two evaluation methods are presented: the objective one (mathematical metrics) and an expert (visual perception) evaluation to measure the performance of the different approaches. Results conclude that ReLU outperforms other activation functions, while Mish and Leaky ReLU perform poorly, and Swish’s professional evaluations highlight a gap between mathematical metrics and human visual perception.

Located in the south of the Iberian Peninsula, the Doñana salt marshes occupy around half of Doñana National Park and are currently considered among the most important wetlands worldwide due to the importance of their ecosystem. In this research work, using a novel patented procedure, the effects of climate change on the study area between 2009 and 2020 were evaluated. For this reason, DEMs were downloaded from the 30-meter Shuttle Radar Topography Mission (SRTM). Furthermore, to check the depth of the flooded area, 792 satellite images (L5 TM, L7 ETM+, and L8 OLI) with a resolution of 30 m were analyzed. The results show how the combined use of geomatic techniques, such as radar, optical, and geographic information system (GIS) data, along with regression models and iterative processes, plays a key role in the prediction and analysis of the flooded area volume in the Doñana salt marshes. Another significant contribution of this work is the development of a new remote sensing index. In conclusion, given that the study area depends on its aquifers’ status, it would be advisable to implement policies aimed at eradicating illegal aquifer extraction, as well as recovery plans to avoid the complete clogging of this salt marsh.

Electric vehicle technology is transitioning from mobility based on fossil fuel combustion to one based on vehicle electrification, in which the primary energy is increasingly renewable, and the generation of pollutants and CO2 emissions is being reduced. This paper provides a tour of the key aspects of these systems, reviewing their most important historical, legislative, and grid impact topics. For this purpose, a literature review of publications up to 2022 is conducted. The last decade is the subject of a deeper analysis, shedding light on the essential characteristics of this technology and fundamentally focusing on its integration into electrical distribution networks. This work is carried out based on a review of a selection of articles written by authors worldwide who have researched these topics. We ordered and analyzed the temporal evolution of the defined categories, obtaining their research line direction. A meta-analysis of grid impact was also carried out, prompting clear conclusions about the state of the art and potential future works.

Concrete is widely utilized across various industries as a containment material. One essential property related to its performance is permeability, which determines its ability to allow the passage of gases or liquids through its pores and capillaries and even the transmission of aggressive agents. This study focused on investigating the permeability of gases with varying atomic weights and molecular volumes, such as helium, nitrogen, oxygen, and argon, to pass through concrete. The primary objective was to determine the significance of variation in permeability and to evaluate and differentiate their behavior. To achieve this, concrete test specimens were employed, and factors such as cold joint impact, gas pressure, and specimen saturation levels were considered. Throughout the study, changes in weight, specimen humidity, resistivity, and ultrasonic pulse velocity were monitored. The findings suggested that within concrete, the variation in permeability for these gases is negligible. By utilizing the acquired data, the present study estimated the permeability of hydrogen through mathematical models based on gas pressure and concrete thickness. These insights contribute to a deeper comprehension of concrete gas permeability and its potential impact on improving hydrogen containment.

Thin films of lithium spinel ferrite, LiFe5O8, have attracted much scientific attention because of their potential for efficient excitation, the manipulation and propagation of spin currents due to their insulating character, high-saturation magnetization, and Curie temperature, as well as their ultra-low damping value. In addition, LiFe5O8 is currently one of the most interesting materials in terms of developing spintronic devices based on the ionic control of magnetism, for which it is crucial to control the lithium’s atomic content. In this work, we demonstrate that dual ion beam sputtering is a suitable technique to tailor the lithium content of thin films of lithium ferrite (LFO) by using the different energies of the assisting ion beam formed by Ar+ and O2+ ions during the growth process. Without assistance, a disordered rock-salt LFO phase (i.e., LiFeO2) can be identified as the principal phase. Under beam assistance, highly out-of-plane-oriented (111) thin LFO films have been obtained on (0001) Al2O3 substrates with a disordered spinel structure as the main phase and with lithium concentrations higher and lower than the stoichiometric spinel phase, i.e., LiFe5O8. After post-annealing of the films at 1025 K, a highly ordered ferromagnetic spinel LFO phase was found when the lithium concentration was higher than the stoichiometric value. With lower lithium contents, the antiferromagnetic hematite (α-Fe2O3) phase emerged and coexisted in films with the ferromagnetic LixFe6-xO8. These results open up the possibility of controlling the properties of thin lithium ferrite-based films to enable their use in advanced spintronic devices.

Volcaniclastic accumulations in shallow marine environments are prone to be eroded and transported by sedimentary agents and then resedimented either on contemporaneous or younger substrates. Therefore, dating of the volcanic events through the sediments containing interbedded volcanic layers can lead to errors. A case study of volcanism in the southeastern Iberian Range during the Early and Middle Jurassic is presented. Precise dating of hosting carbonate sediments based on ammonite and brachiopod biochronostratigraphic method has allowed distinguishing 13 volcanic levels of different ages ranging from the early Pliensbachian to the early Bajocian. A set of petrological, geomorphological, sedimentological, and paleontological criteria are applied in order to discriminate primary from secondary (epiclastic) volcaniclastic deposits and thus make it possible to match the ages of primary volcaniclastic deposits with volcanic eruptions. Implementation of such criteria has confirmed that the early Pliensbachian–early Bajocian interval (ca. 20 Ma) corresponds with the actual period of volcanic activity.

Abstract Many of the rarest prehistoric bones found by archaeologists are enormously precious and are considered to be part of our cultural and historical patrimony. Radiocarbon dating is a well-established technique that estimates the ages of bones by analysing the collagen still present. However, this method is destructive, and its use must be limited. In this study, we used imaging technology to quantify the presence of collagen in bone samples in a non-destructive way to select the most suitable samples (or sample regions) to be submitted to radiocarbon dating analysis. Near-infrared spectroscopy (NIR) that was connected to a camera with hyperspectral imaging (HSI) was used along with a chemometric model to create chemical images of the distribution of collagen in ancient bones. This model quantifies the collagen at every pixel and thus provides a chemical mapping of collagen content. Our results will offer significant advances for the study of human evolution as we will be able to minimise the destruction of valuable bone material, which is under the protection and enhancement of European cultural heritage and thus allow us to contextualise the valuable object by providing an accurate calendar age.

Red wines and their pomace are valuable sources of phenolic compounds (PCs), which have been proposed as potential contributors to their cardioprotective effect through the inhibition of platelet aggregation. The antiplatelet activity of an extract depends on its chemical composition, specifically the presence of certain phenolic compounds, as well as the interactions between them affecting biological activity. In order to assess the effect on platelet aggregation, we investigated the effect of the grape pomace PC enrichment of a Merlot wine, as well as the effect of the five major phenolic compounds present in wine extracts: caffeic acid, gallic acid, quercetin, epicatechin, and catechin. We analyzed how their combination influenced platelet aggregation. We found that the fortified wine sample with the highest PC content (W8) exhibited a potent antiplatelet effect in aggregation and platelet activation assays induced by the agonists TRAP-6, collagen, and ADP, with its activity being most potent against the latter agonist (78 ± 4%). Among the evaluated phenolic compounds, quercetin showed the highest antiplatelet potential against all three agonists studied, while gallic acid showed minimal antiplatelet effect. These findings suggest that the cardioprotective effect of wines is related to their chemical composition and the synergy among phenolic compounds. However, further research is required to fully understand the underlying mechanisms and clinical relevance of this activity.

In the Pistoia Nursery-Ornamental Rural District (Italy), a leader in Europe in ornamental nurseries covering over 5200 hectares with over 2500 different species of plant, plant-parasitic nematodes represent a serious concern. The potential efficacy of a pot cultivation system using commercial substrates to control plant-parasitic nematodes was assessed. On two different plant species, two different pot cultivation managements, potted plants, and potted plants previously cultivated in natural soil were compared to plants only cultivated in natural soil. The entire soil nematode structure with and without plants was evaluated. The relationship between soil properties and soil nematode community was investigated. All the studied substrates were free from plant-parasitic nematodes. Regarding free-living nematodes, Peat–Pumice showed nematode assemblage established by colonizer and extreme colonizer bacterial feeders, whereas Peat–Perlite included both bacterial and fungal feeders, and, finally, coconut fiber also included omnivores and predators. In farming, the substrates rich in organic matter such as coconut fiber could still play an important role in suppressing plant-parasitic nematodes because of the abundance of free-living nematodes. In fact, they are of crucial importance in both the mineralization of organic matter and the antagonistic control of plant-parasitic nematodes. Potting systems equally reduce virus-vector nematodes and improve the prey/predator ratio favoring natural control.

Cigarette butts (CBs) are non-biodegradable harmful residues of synthetic origin and are widespread in marine environments around the world. Although environmental factors are often primarily responsible for the fragmentation of microplastics in the marine environment, biotic factors have recently been shown to be equally important in plastic debris. This study evaluates the role of the Hediste diversicolor polychaete in the fragmentation of CBs in the marine environment. Polychaetes were exposed to three concentrations of CB (0 (as the control), 0.25, and 1 butt L−1) at two different temperatures (15 °C and 23 °C) for 28 days. At each temperature, aquaria without polychaetes were used to study the effect of the burrowing activity of the polychaete on CB fragmentation. Toxicants analysed from exposed sediments increased their concentration in a dose-dependent manner to the CB concentration at a temperature of 15 °C but not at 23 °C. CBs did not directly decrease Hediste survival, but prolonged elevated temperatures increased the polychaetes’ susceptibility. The negative effects of CBs on burial success and burrowing behaviour could not be offset by the reduced start time caused by elevated temperatures. Regardless of temperature, both the weight loss and physical fragmentation of CBs buried in polychaete-contaminated sediments were significantly higher than those without Hediste, with no differences between the two concentrations tested. FTIR-ATR analysis used to evaluate CB degradation in relation to cellulose acetate decomposition showed a greater degradation of this compound in treatments with Hediste than in those without polychaetes (~2.75 times), but these differences were not significant. This study is a promising initial step for future research, as any factor that facilitates the fragmentation of this prevalent and hazardous waste must be carefully studied to extract the maximum benefit to help to reduce CBs in the marine environment.

Hospitals have demonstrated their enormous capacity to adapt to the rapidly changing situation imposed by the pandemic: increasing the number of intensive care units and intermediate and inpatient beds, with the corresponding human resources, services and facilities required. Internationally, the enormous demand to manage the COVID-19 pandemic has challenged hospitals in terms of staffing, supplies and equipment. This article analyses the effect of the COVID-19 pandemic on hospital activities, from the perspective of its environmental impact. It compares a year of normal hospital activities, 2019, with data on hospital activities from 2020. The aim of this research is to analyse the changes produced by the pandemic in the regular activities of the hospital and to determine the environmental impact, which allows reflecting on the exceptional situation generated. The results show that the hospital’s environmental impact increased significantly in 2020 compared to 2019, with a 17.2% increase in overall environmental efficiency indices. The main contributors to this increase were waste generation and medical gas consumption, which are critical aspects of hospital activities during the pandemic.

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

Objective: The current study’s objective is to characterize a new throm-bin-like enzyme called TLBro that was obtained from Bothrops roedingeris snake from a biochemical and hemostatic perspective.Methodology: One chromatographic step was used to purify it, producing the serine protease TLBro. Molecular mass was estimated by SDS-PAGE to be between reduced and unreduced by 35 kDa. Tryptic peptide sequencing using Swiss Prot provided the complete amino acid sequence. Expasy.org by conducting a search that is limited to Crotalinae snake serine proteases and displaying a high degree of amino acid sequence.Results: Ser (182) is inhibited by phenylmethylsulfonyl fluoride (PMSF), and TLBro demonstrated the presence of Asp (88) residues. It also deduced the positions of His (43) and Ser (182) in the set of three coordinated amino acids in serine proteases. It was discovered that this substrate had high specificity for BANA, Michaelis-Menten behavior with KM 0 point85 mM and Vmax 1 point89 nmoles -NA/L/min, and high stability between temperatures (15 to 70°C) and pHs (2 point0 to 10 point0). According to doses and incubation times, TLBro degraded fibrin preferentially on the B-chain; additionally, its activities were significantly diminished after preincubation with divalent ions (Zn2 and Cd2). When incubated with PMSF, a particular serine protease inhibitor, enzymatic activities and platelet aggregation were inhibited.Conclusion: The findings revealed distinct structural and functional differences between the serine proteases, adding to the information and assisting in the improvement of the structure-function relationship.

The development of direct dimethyl ether (DME) solid oxide fuel cells (SOFCs) has several drawbacks, due to the low catalytic activity and carbon deposition of conventional Ni–zirconia-based anodes. In the present study, the insertion of 2.0 wt.% Ru-Ce0.7Zr0.3O2−δ (ruthenium–zirconium-doped ceria, Ru-CZO) as an anode catalyst layer (ACL) is proposed to be a promising solution. For this purpose, the CZO powder was prepared by the sol–gel synthesis method, and subsequently, nanoparticles of Ru (1.0–2.0 wt.%) were synthesized by the impregnation method and calcination. The catalyst powder was characterized by BET-specific surface area, X-ray diffraction (XRD), field emission scanning electron microscopy with an energy-dispersive spectroscopy detector (FESEM-EDS), and transmission electron microscopy (TEM) techniques. Afterward, the catalytic activity of Ru-CZO catalyst was studied using DME partial oxidation. Finally, button anode-supported SOFCs with Ru-CZO ACL were prepared, depositing Ru-CZO onto the anode support and using an annealing process. The effect of ACL on the electrochemical performance of cells was investigated under a DME and air mixture at 750 °C. The results showed a high dispersion of Ru in the CZO solid solution, which provided a complete DME conversion and high yields of H2 and CO at 750 °C. As a result, 2.0 wt.% Ru-CZO ACL enhanced the cell performance by more than 20% at 750 °C. The post-test analysis of cells with ACL proved a remarkable resistance of Ru-CZO ACL to carbon deposition compared to the reference cell, evidencing the potential application of Ru-CZO as a catalyst as well as an ACL for direct DME SOFCs.

We have studied the stochastic processes A and B concerning fade durations due to rain, by simulating attenuation time series A(t) (dB) in the zenith paths of GeoSurf satellite constellations, at sites located in different climatic regions, with the Synthetic Storm Technique. Process B gives the statistics of outages (occurrences) and process A gives the statistics of outage duration (fraction of time), for the same rain attenuation threshold A(t)>S. The two processes are not independent; therefore, we have studied the relationship between their probabilities and defined a uniformity index 0

In recent years, the use of techniques based on electromagnetic radiation as an investigative tool in the agri-food industry has grown considerably, and between them, the application of imaging and THz spectroscopy has gained significance in the field of food quality control. This study presents the development of an experimental setup operating in transmission mode within the frequency range of 18 to 40 GHz, which was specifically designed for assessing various quality parameters of hazelnuts. The THz measurements were conducted to distinguish between healthy and rotten hazelnut samples. Two different data analysis techniques were employed and compared: a traditional approach based on data matrix manipulation and curve fitting for parameter extrapolation, and the utilization of a Self-Organizing Map (SOM), for which we use a neural network commonly known as the Kohonen neural network, which is recognized for its efficacy in analyzing THz measurement data. The classification of hazelnuts based on their quality was performed using these techniques. The results obtained from the comparative analysis of coding efforts, analysis times, and outcomes shed light on the potential applications of each method. The findings demonstrate that THz spectroscopy is an effective technique for quality assessment in hazelnuts, and this research serves to clarify the suitability of each analysis technique.

One-dimensional (1D) magnetic systems offer rich phenomena in the quantum limit, proving more chemically accessible than zero-dimensional or higher-dimensional frameworks. Single-walled carbon nanotubes (SWCNT) have recently been used to encapsulate trimetric nickel(II) acetylacetonate [Nanoscale, 2019, 11, 10615–10621]. Here, we investigate the magnetization on spin chains based on nickel trimers by Matrix Product State (MPS) simulations. Our findings reveal plateaus in the exchange/magnetic-field phase diagram for three coupling configurations, showcasing effective dimeric and trimeric spin-ordering with similar or staggered entanglement across chains. These ordered states allow the qubit-like tuning of specific local magnetic moments, exhibiting disengagement or uniform coupling in entanglement plateaus. This behavior is consistent with the experimental transition from frustrated (3D) to non-frustrated (1D) molecules, corresponding to large and smaller SWCNT diameters. Our study offers insights into the potential of 1D-confined trimers for quantum computation, extending beyond the confinement of trimetric nickel-based molecules in one dimension.

The use of organic fertilizers to replace chemically synthesized fertilizers has assumed an important role in managing plant nutrition and soil fertility. The various organic matrices currently available as organic byproducts and digestates are relatively abundant and have shown promising effects in terms of plant-available nutrients. However, like mineral fertilizers, organic fertilizers must be carefully managed to avoid negative effects on the environment, especially when they are repeatedly applied over time. The aim of the present study was to assess the effect of the single (DIG) and repeated application (DIGP) of solid anaerobic digestates compared to an unamended control (CTR) on the denitrifying enzymatic activity (DEA), which is responsible for nitrous oxide emissions into the atmosphere, and some related soil properties, such as total soluble nitrogen (TSN), nitrate (NO3−-N), extractable carbon (Cextr), microbial biomass carbon (MBC), and basal respiration (Rbas), for a period of ~3 months after application. The application of solid anaerobic digestates progressively boosts N and C concentrations in the soil, with the degree of enhancement directly correlated with the frequency of application over the sampling period. Depending on the textural properties of soils, there was a notable rise in denitrification enzyme activity (DEA), particularly during the DIGP treatment, suggesting that clay soils are highly susceptible to denitrification under suitable conditions. The results of this study recommend the careful management of soils subjected to repeated digestate amendment to prevent the occurrence of conditions conducive to denitrification and the promotion of N2O emissions.

Physical activity analysis assessment has been a concern throughout human history. The intersection of technological growth with sports has given rise to a burgeoning field known as sports engineering. In the 19th century, the advent of chrono-photography and pioneering marked the inception of sports performance analysis. In recent years, the noticeable developments achieved in wearable low-power electronics with wireless high interconnection capability, as a part of modern technologies, have aided us in studying sports parameters such as motor behavior, biomechanics, equipment design, and materials science, playing an essential role in the understanding of sports dynamics. This study aims to review over 250 published articles since 2018, focusing on utilizing and validating these emergent technologies in sports and clinical aspects. It is predicted that one of the next steps in sports technology and engineering development will be using algorithms based on artificial intelligence to analyze the measurements obtained by multi-sensor systems (sensor fusion) to monitor biometric and physiological parameters in performance analysis and health assessments.

MOOCs (massive open online courses) are popular distance courses for which anyone can sign up online with no limits on the number of participants. Moreover, artificial intelligence is a combination of algorithms for the development of human and rational capabilities by machines. This article presents a quantitative study with a sample of 734 MOOCs on artificial intelligence from three important platforms. Through exploratory and factor analyses, and with the support of a category system, it is concluded that, there are similarities in terms of access to content, ease of navigation, design, toolbars, consistency, visible hypertexts, browsing support and links, help in content searching, and course development with regard to the technical dimension. Regarding the pedagogical dimension, xMOOCs represent the most extensive international trend, and unidirectional resources predominate. In relation to the content dimension, MOOCs that include content on the emerging and current uses of artificial intelligence in learning and training are remarkable, including three main trends in MOOCs on artificial intelligence: machine learning and education, ethics of AI, and human learning and inclusivity.

To establish classifications and to obtain pre- and post-operative information on patient-specific alignments, it is necessary to measure different angular values accurately and precisely, mainly on weight-bearing, full-length anteroposterior X-rays of the lower limbs (LLRs). This study evaluated angular measurements’ validity and absolute reliability on LLRs with a self-developed, computer-aided measurement system (TraumaMeter v.873). Eight independent observers measured the preoperative mechanical hip-knee-ankle (mHKA) angle of 52 lower extremities (26 cases) in a blinded fashion on three occasions separated by two weeks. We obtained an intra-observer mean bias error (MBE) of 0.40°, a standard deviation (SD) of 0.11°, and a 95% confidence interval (CI) of 0.37°–0.43°. We also obtained an inter-observer MBE of 0.49°, an SD of 0.15°, and a 95% C of 0.45°–0.53°. The intra-observer MBE for the measurement pair between the second and the first measurement round (T2T1) was 0.43°, the SD was 0.13°, and the 95% CI was 0.39°–0.47°; the MBE between the third and the second round (T3T2) was 0.37°, with an SD of 0.10° and a 95% CI of 0.34°–0.40°; and the MBE between the third and the first round (T3T1) was 0.40°, with an SD of 0.10° and a 95% CI of 0.37°–0.43°. The interobserver MBE for the first round of measurements was 0.52°, with an SD of 0.16° and a 95% CI of 0.48°–0.56°; the MBE for the second round was 0.50°, with an SD of 0.15° and a 95% CI of 0.46°–0.54°; and the MBE for the third round was 0.46°, with an SD of 0.14° and a 95% CI of 0.42°–0.50°. There were no statistically significant differences in the inter-observer errors for the three tests. In the case of the intra-observer analysis, there were differences between T2T1 and between T3T2, but these differences were minimal, with no overlaps in the lower or upper values, respectively, of the confidence intervals. These results led us to conclude that the TraumaMeter v.873 software extension for measuring lower-limb angles in LLRs is an accurate tool with low intra- and inter-observer variability.

Climate change mitigation requires the development of greener chemical processes. In this context, biocatalysis is a pivotal key enabling technology. The advantages of biocatalysis include lower energy consumption levels, reduced hazardous waste production and safer processes. The possibility to carry out biocatalytic reactions under flow conditions provides the additional advantage to retain the biocatalyst and to reduce costly downstream processes. Herein, we report a method to produce galactooligosaccharides (GOSs) from a largely available feedstock (i.e. lactose from dairy production) using a flow reactor based on hierarchically structured monolithic silica. This reactor allows for fast and efficient biotransformation reaction in flow conditions.

Healthcare services and institutions are focused on providing the most appropriate medical service in terms of patient safety and satisfaction outcomes. According to Lean methodologies, effectiveness and efficiency can be improved by assuring value-added processes. This article presents a joint approach for the development and implementation of Lean techniques combined with Total Laboratory Automation (TLA) for serology diagnosis in a microbiology laboratory in a tertiary-level hospital. The results obtained show an improvement in the process efficiency and its key performance indicators. In particular, for the HIV and COVID tests, the process Turnaround Times (TAT) were decreased by up to 87.3% and 19.3%, having a direct effect in the diagnostic response time. The process added-value for HIV tests increased by 81%. This meant a cost reduction per test, a higher number of diagnostic tests and clinical samples processed and laboratory resource optimisation. The implementation of TLA also enabled the reallocation of skilled labour towards value-added tasks, increased the process quality and reduced sample waiting times. This work opens up new opportunities for their deployment in other laboratory areas and sample types, directly influencing the overall quality of patient diagnosis in the context of tertiary healthcare facilities.

Bone and cartilage tissue play multiple roles in the organism, including kinematic support, protection of organs, and hematopoiesis. Bone and, above all, cartilaginous tissues present an inherently limited capacity for self-regeneration. The increasing prevalence of disorders affecting these crucial tissues, such as bone fractures, bone metastases, osteoporosis, or osteoarthritis, underscores the urgent imperative to investigate therapeutic strategies capable of effectively addressing the challenges associated with their degeneration and damage. In this context, the emerging field of tissue engineering and regenerative medicine (TERM) has made important contributions through the development of advanced hydrogels. These crosslinked three-dimensional networks can retain substantial amounts of water, thus mimicking the natural extracellular matrix (ECM). Hydrogels exhibit exceptional biocompatibility, customizable mechanical properties, and the ability to encapsulate bioactive molecules and cells. In addition, they can be meticulously tailored to the specific needs of each patient, providing a promising alternative to conventional surgical procedures and reducing the risk of subsequent adverse reactions. However, some issues need to be addressed, such as lack of mechanical strength, inconsistent properties, and low-cell viability. This review describes the structure and regeneration of bone and cartilage tissue. Then, we present an overview of hydrogels, including their classification, synthesis, and biomedical applications. Following this, we review the most relevant and recent advanced hydrogels in TERM for bone and cartilage tissue regeneration.

In recent years, the rapid growth of virtual reality has opened up new possibilities for creating immersive virtual worlds known as metaverses. With advancements in technology, such as virtual reality headsets, and the emergence of applications with social interaction, metaverses offer exciting opportunities for STEM (Science, Technology, Engineering, and Mathematics) education. This article proposes the integration of metaverses into STEM courses, enabling students to forge connections between different subjects within their curriculum, to leverage current technological advancements, and to revolutionize project presentations and audience interaction. Drawing upon a case study conducted with students enrolled in the “Proyectos RII 1: Organización y Escenarios” course at the Escuela Politécnica Superior de Alcoy of the Technical University of Valencia (Spain), this article provides a comprehensive description of the methodology employed by the students and professors. It outlines the process followed, shedding light on the innovative use of metaverses in their projects. Moreover, the article shares valuable insights obtained through surveys and personal opinions gathered from students throughout the course and upon its completion. By exploring the intersection of metaverses and STEM education, this study showcases the transformative potential of integrating interactive virtual environments. Furthermore, this work highlights the benefits of increased student engagement, motivation, and collaboration, as well as the novel ways in which projects can be presented and interactions with audiences can be redefined.

There is clear evidence of the effects of air pollution on health. In this paper, we present an innovative application designed to assess Air Quality (AQ) exposure based on the World Health Organization’s AQ Guidelines, analysing pollutants and their concentrations independently. Our aim is to provide this information to citizens based on their health profile (medical history or requirements) before and during outdoor trips of their choice, both walking and cycling, empowering them to proactively make informed personal decisions about their route choices and identifying potentially unhealthy travel environments. For this purpose, we have access to official data from AQ monitoring stations that are updated periodically every 10 min. Then, by using spatial interpolation techniques (with Ordinary Kriging), we estimate each pollutant over a grid superimposed on the city map. Once the pollutants have been mapped on each route, they are analysed in order to consider the different alternatives for deciding and planning changes in speed or trajectory. We evaluated the application in the city of Valencia (Spain) as a use case under different scenarios, and showed the results to assess exposure to pollution on the routes of citizens.

OEMT is an existing optimizing envelope method for thin-film characterization that uses only one transmittance spectrum, T(λ), of the film deposited on the substrate. OEMT computes the optimized values of the average thickness, d¯, and the thickness non-uniformity, Δd, employing variables for the external smoothing of T(λ), the slit width correction, and the optimized wavelength intervals for the computation of d¯ and Δd, and taking into account both the finite size and absorption of the substrate. Our group had achieved record low relative errors, d¯ of thin semiconductor films via OEMT, whereas the high accuracy of d¯ and Δd allow for the accurate computation of the complex refractive index, N˙(λ), of the film. In this paper is a proposed envelope method, named OEMR, for the characterization of thin dielectric or semiconductor films using only one quasi-normal incidence UV/Vis/NIR reflectance spectrum, R(λ), of the film on the substrate. The features of OEMR are similar to the described above features of OEMT. OEMR and several popular dispersion models are employed for the characterization of two a-Si films, only from R(λ), with computed d¯ = 674.3 nm and Δd = 11.5 nm for the thinner film. It is demonstrated that the most accurate characterizations of these films over the measured spectrum are based on OEMR.

Hole-transporting materials (HTMs) have demonstrated their crucial role in promoting charge extraction, interface recombination, and device stability in perovskite solar cells (PSCs). Herein, we present the synthesis of a novel dopant-free spiro-type fluorine core-based HTM with four ethoxytriisopropylsilane groups (Syl-SC) for inverted planar perovskite solar cells (iPSCs). The thickness of the Syl-SC influences the performance of iPSCs. The best-performing iPSC is achieved with a 0.8 mg/mL Syl-SC solution (ca. 15 nm thick) and exhibits a power conversion efficiency (PCE) of 15.77%, with Jsc = 20.00 mA/cm2, Voc = 1.006 V, and FF = 80.10%. As compared to devices based on PEDOT:PSS, the iPSCs based on Syl-SC exhibit a higher Voc, leading to a higher PCE. Additionally, it has been found that Syl-SC can more effectively suppress charge interfacial recombination in comparison to PEDOT:PSS, which results in an improvement in fill factor. Therefore, Syl-SC, a facilely processed and efficient hole-transporting material, presents a promising cost-effective alternative for inverted perovskite solar cells.

MOLECULAR SYMMETRY AND DESYMMETRIZATION REACTIONS IN ORGANIC SYNTHESIS. Molecular Symmetry has found several applications in Organic Chemistry. The aim of this article is to showcase its relevance as a tool for synthetic planning. Natural Products and synthetic compounds with pharmaceutical applications were selected to highlight desymmetrization reactions that make use of organocatalysis, biocatalysis or by transition metals. The recognition of structural patterns in retrosynthetic analysis is discussed for compounds that exhibit explicit or hidden symmetry. Limitations of the aforementioned strategies are also described, as well as the untapped potential, challenges and frontiers yet to be explored regarding these concepts.

Cadherins promote cell-cell adhesion by forming homophilic interactions via their N-terminal extracellular domains. Hence, they have broad-ranging physiological effects on tissue organization and homeostasis. When dysregulated, cadherins contribute to different aspects of cancer progression and metastasis; therefore, targeting the cadherin adhesive interface with small-molecule antagonists is expected to have potential therapeutic and diagnostic value. Here, we used molecular docking simulations to evaluate the propensity of three different libraries of commercially available drug-like fragments (nearly 18,000 compounds) to accommodate into the Trp2 binding pocket of E-cadherin, a crucial site for the orchestration of the protein’s dimerization mechanism. Top-ranked fragments featuring five different aromatic chemotypes were expanded by means of a similarity search on the PubChem database (Tanimoto index >90%). Of this set, seven fragments containing an aromatic scaffold linked to an aliphatic chain bearing at least one amine group were finally selected for further analysis. Ligand-based NMR data (Saturation Transfer Difference, STD) and molecular dynamics simulations suggest that these fragments can bind E-cadherin mostly through their aromatic moiety, while their aliphatic portions may also diversely engage with the mobile regions of the binding site. A tetrahydro-β-carboline scaffold functionalized with an ethylamine emerged as the most promising fragment.

Purse-seine yellowfin tuna (Thunnus albacares) catch and effort data and satellite monthly composite images of the Advanced Very High Resolution Radiometer (AVHRR) derived sea surface temperature (SST) were used to examine the relationship between the aggregation of yellowfin and the distribution of SST in the eastern tropical Pacific during the period 1995-2003. Monthly catch per unit effort (CPUE) values were calculated as the catch in metric tonnes/number of fishing days in a 1º latitude x 1º longitude grid and used as the relative abundance index. In total, 33,542 purseseine yellowfin CPUE data were used. Results obtained allow establishing the SST range between 26ºC and 30ºC as the “preferred” thermal range for yellowfin tuna in the eastern tropical Pacific, and the SST range between 28ºC and 30ºC as the most favorable SST range of yellowfin fishing success. The consistent occurrence of yellowfin tuna in the relatively shallow mixed surface layer (≈40-50 m) of homogeneous temperature predominant in the eastern tropical Pacific suggests that the “preferred” SST range for yellowfin found in this study may be representative of the optimal thermal habitat of this species.

Proposes a simple procedure based on an expansion of the exponential terms of Raoult's law by applying it to the case of the benzene-toluene mixture. The results with experimental values are presented as a table. (YP)

This work proposes a differential evolution algorithm to control a vehicle-to-grid (V2G) system based on photovoltaic generation and energy cost curves, and constraints associated with the power converters’ operation, battery charging strategy, and initial budgets. The algorithm is designed to trade off the batteries’ state of charge and the profits gained from selling energy to the grid. To achieve this balance, a fuzzy controller is employed and acts based on forecasts of the photovoltaic generation and the cost of electricity, within prediction windows of 120 min, adapting the batteries’ rate of charging or discharging. Simulation results show that for different curves and different initial budgets, the target state of charge is reached at the end of the time horizon. By evaluating the proposed scheme under different scenarios, the algorithm’s performance is proven to be suitable for future practical deployment.

The temperature-dependent luminescence properties of γ-Ga2O3 nanoparticles prepared by a precipitation method are investigated under steady-state and pulsed-light excitation. The main photoluminescence (PL) emission at room temperature consists of a single blue band centered around 2.76 eV, which hardly undergoes a blueshift of 0.03 eV when temperature goes down to 4 K. The emission behaves with a positive thermal quenching following an Arrhenius-type curve. The data fitting yields two non-radiative levels affecting the emission band with activation energies of 7 meV and 40 meV. On the other hand, time-resolved PL measurements have also been taken and studied as a function of the temperature. The data analysis has resulted in two lifetimes: one of 3.4 ns and the other of 32 ns at room temperature, which undergo an increase up to 4.5 ns and 65 ns at T = 4 K, respectively. Based on both stationary and dynamic PL results, a model of radiative and non-radiative levels associated with the main emission bands of γ-Ga2O3 is suggested. Finally, by using PL excitation measurements, an estimation of the bandgap and its variation with temperature between 4 K and room temperature were obtained and assessed against O’Donnell–Chen’s law. With this variation it has been possible to calculate the average of the phonon energy, resulting in ⟨ħω⟩ = 10 ± 1 meV.