Metabolic bone diseases cover a broad spectrum of disorders that share alterations of bone metabolism leading to a defective skeleton, associated with increasing morbidity, disability, and mortality. There is a close connection between the etiology of metabolic bone diseases and genetic factors, being TP53 one of the genes associated therewith. The single nucleotide polymorphism (SNP) Arg72Pro of TP53 is a genetic factor associated with several pathologies, including cancer, stroke and osteoporosis. Here, we aim to analyze the influence of the TP53 Arg72Pro SNP on bone mass in the humanized Tp53 Arg72Pro knock-in mice. This work reported on the influence of TP53 Arg72Pro polymorphism in bone microarchitecture, OPG gene expression and apoptosis bone status. The results showed that the proline variant of TP53 Arg72Pro polymorphism (Pro72-p53) was associated with deteriorated bone tissue, lower OPG/RANK ratio and lower apoptosis in bone tissue. In conclusion, the TP53 Arg72Pro polymorphism modulates bone microarchitecture and may be a genetic biomarker to identify individuals with an increased risk of suffering metabolic bone alterations

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

Soil amendments with composted organic materials are recommended to increase soil organic matter (SOM), promote soil fertility, and the Circular Economy. Growing areas of hedged olive groves in southern Iberia peninsula generate huge amounts of olive leaves whose potential as soil organic amendment is not fully studied. An experimental field trial in a hedged olive grove (cv. “Cobrançosa”) was set up near Portalegre, Portugal, to test a compost of olive leaves plus sheep manure (2:1) applied in the row, at soil surface. Three nominal rates (0 or control, 2.5 and 5.0 kg m-2) were used, in a complete randomized block setup (3 treatments, 3 replicas, 9 plots) and soil chemical properties of layers 0-5, 5-15, and 15-30 cm deep were annually monitored. Results (mainly in layer 0-5 cm) showed increases in total N, carbon of the particulate organic matter (POM-C), permanganate oxidizable carbon (POX-C), extractable phosphorus, and zinc, after one year, and increases in soil organic carbon (SOC), C-stock, pHKCl, extractable phosphorus, and zinc, after two years. POX-C was the most sensitive SOM-related indicator, showing increases up to 30 cm deep after one year. This compost improved soil fertility, but should be monitored over longer periods of time, namely for SOC and extractable zinc content.

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

Shot peening is an attractive technique for fatigue enhanced performance of metallic components, because it promotes crack initiation retardation and later crack growth. Engineering design based on fatigue crack propagation predictions applying the principles of fracture mechanics is commonly used in aluminum structures for aerospace engineering. The main purpose of present work was to analyze the effect of shot peening on the fatigue crack propagation of the 7475 aluminum alloy, under both constant amplitude loading and periodical overload blocks. The tests were performed on 4 and 8 mm thickness specimen's with stress ratios of 0.05 and 0.4. The analysis of the shot-peened surface showed a small increase of the micro-hardness values, due to the plastic deformations imposed by shot peening. The beneficial effect of surface peening on fatigue crack growth rates is quite limited to an increasing near the threshold. The specimens’ thickness has only marginal influence on the crack propagation, in opposite to the stress ratio. Periodic overload blocks of 300 cycles promotes a reduction of the fatigue crack growth rate for both intervals of 7,500 and 15,000 cycles.

Non-toroidal shape primary pass through protection current transformers (CTs) are used to measure high currents. Their design provides them with a big airgap that allow passing several cables per phase though them, which is the main advantage versus toroidal types, as the number of CTs required to measure the whole phase current is drastically reduced. The cables pass through the transformer window can be in several positions. As the isolines of the magnetic field generated by the primary currents are centered in the cables, if these cables are not centered in the transformer window, the magnetic field will be non-uniform along the transformer core. Consequently, local saturations can appear if the cables are not properly disposed causing the malfunction of the CT. In this paper, the performance of a non-toroidal shape protection CT is studied. The research is focused on the cable position influence in possible partial saturations of the CT when it is operating near to its accuracy limit. Depending on the cable position, the ratio of the primary and secondary currents can depart from assigned ratio. The validation of this phenomenon has been carried out via Finite Element Analysis (FEA) showing that partial transformer core saturations appears in areas of the magnetic core close to the cable. Applying FEA, also the admissible accuracy region for cable positioning inside the CT is delimited. Finally, the simulation results are ratified with experimental tests performed in non-toroidal protection CTs varying the primary cables’ positions, which are subjected to currents up to 5 kA, achieving satisfactory results. From this analysis, installation recommendations are given.

This paper presents a comprehensive investigation into the applicability and performance of two prominent growth models, namely the Verhulst model and the Montroll model, in the context of modeling tumor cell growth dynamics. Leveraging the power of Physics-Informed Neural Networks (PINNs), we aim to assess and compare the predictive capabilities of these models against experimental data obtained from the growth patterns of tumor cells. We employ a dataset comprising detailed measurements of tumor cell growth to train and evaluate the Verhulst and Montroll models. By integrating PINNs, we not only account for experimental noise but also embed physical insights into the learning process, enabling the models to capture the underlying mechanisms governing tumor cell growth. Our findings reveal the strengths and limitations of each growth model in accurately representing tumor cell proliferation dynamics. Furthermore, the study sheds light on the impact of incorporating physics-informed constraints on the model predictions. The insights gained from this comparative analysis contribute to advancing our understanding of growth models and their applications in predicting complex biological phenomena, particularly in the realm of tumor cell proliferation.

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

On the system Au(III)-HCl-A324H⁺Cl^-, liquid-liquid extraction experiments were used to define the extraction equilibrium and the corresponding extraction constant, and the facilitated transport of this precious metal, from HCl solutions, across a flat-sheet supported liquid membrane was investigated, using the ionic liquid as carrier, as a function of hydrodynamic conditions, concentration of gold(III) (0.01-0.1 g/L), and HCl (0.5-6 M) in the feed phase, and carrier concentration (0.023-0.92 M) in the membrane. An uphill transport equation was derived considering aqueous feed boundary layer diffusion and membrane diffusion as controlling steps. The aqueous diffusional resistance (Δf) and the membrane diffusional resistance (Δm) were estimated from the proposed equation, being their values 241 s/cm an 9730 s/cm, respectively. The performance of the present carrier was compared against results yielded by other ionic liquids, and also it was investigated the influence that other metals had on gold(III) transport both from binary or quaternary solutions. Gold was finally recovered from receiving solutions as zero valent gold nanoparticles.

The relationship between Climate Change and Water is an obvious and key issue within the Sustainable Development Goals. This study aims to investigate the social representation created around this relationship in three different territorial contexts in order to evaluate the influence of the territory on the perception of the risk of Climate Change and its relationship with water. By means of a questionnaire completed by 1709 university students, the climatic literacy of the individual was evaluated in order to relate it to other dimensions on the relationship between Climate Change and Water (information, training previous on climate change and pro-environmental attitudes) in their different dimensions in three different territorial contexts. The results show that the socio-cultural context influences the social representation of Climate Change, but not from the climatological condition, so that it is reasonable to think that the social representation of this relationship is favoured by a common culture around this relationship.

Identifying groups that share common features among datasets through clustering analysis is a typical problem in many fields of science, particularly in post-omics and systems biology research. In respect of this, quantifying how a measure can cluster or organize intrinsic groups is important since currently there is no statistical evaluation of how ordered is, or how much noise is embedded in the resulting clustered vector. Many of the literature focuses on how well the clustering algorithm orders the data, with several measures regarding external and internal statistical measures; but none measure has been developed to statistically quantify the noise in an arranged vector posterior a clustering algorithm, i.e., how much of the clustering is due to randomness. Here, we present a quantitative methodology, based on autocorrelation, to assess this problem.

In this work, we report manganese phthalocyanine (MnPc) films obtained by ultrasonic spray-pyrolysis technique at 40°C deposited on glass substrate subjected to thermal annealing at 100 °C and 120°C. The MnPc films were characterized by UV/Vis spectroscopy, Raman spectroscopy, X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). The absorption spectra of the MnPc films were studied in a wavelength range from 200 to 850 nm, where the characteristic bands of a metallic phthalocyanine known as B and Q bands were observed in this range of the spectrum. The optical energy band (Eg) was calculated by the Tauc equation. It was found that for these MnPc films, the Eg has the values of 4.41, 4.46 and 3.58 eV corresponding to as deposited, annealing 100°C and 120°C, respectively. The Raman spectra of the films showed their characteristic vibrational modes of the MnPc films. In X-ray diffractograms of these films, the characteristic diffraction peaks of a metallic phthalocyanine are observed, presenting a monoclinic phase. SEM images of these films were studied in cross section obtaining thicknesses of 2, 1.2 and 0.3 μm to as deposited, annealing 100°C and 120°C, successively. Also, in the SEM images of these films, both the average particle sizes ranging from 4 to 0.041 µm and the average diameter from 4.8 to 0.091 μm were obtained. The results agree with those reported in the literature for MnPc films deposited with other techniques.

In the last decade, the integration of robots into agricultural tasks has significantly transformed food production from planting to harvest. The precision and efficiency of a robot allow for specialized crop management in cases such as; plant disease identification, optimization of water and fertilizer use, monitoring of environmental and soil conditions, among others. That is, the adoption of robots in agricultural practices through intelligent automation increases crop yields and decreases environmental impact. Intelligent automation faces contemporary challenges such as climate change and population growth, promoting sustainable food security. Therefore, this article presents a review of the state of the art of modular robots and their applications in agriculture. Modular robots have the ability to reconfigure and adapt to different tasks, promoting versatile solutions for the agricultural sector. These solutions are linked to the robot's control systems, which can be centralized, decentralized, and hybrid. Firstly, centralized control allows for unified management and coordination in high-precision tasks. Secondly, the decentralized approach offers flexibility and robustness in changing environments where adaptability is required. Thirdly, hybrids incorporate features of both control types balancing control and autonomy to increase efficiency and effectiveness in practical applications. In some cases, control systems incorporate bio-inspired motion control techniques, where the robot mimics natural movements and behaviors to improve its adaptability in performing a task. For example, the chemosynthesis model, which is a biological process where bacteria convert an inorganic compound into energy, has been adapted for individual robots to explore and navigate their environment. Therefore, this article presents an overview of modular robots, the incorporation of bio-inspired motion control techniques, and their convergence towards the sustainable solution of contemporary problems in the agro-industry.

In bone tissue engineering, ceramics have been the choice due to their excellent biological properties. But the paradigm changed with the discovery of bioactive glasses (BGs) in 1969 by Larry Hench and co-workers, due to their ability to bond to living tissues through the formation of an interfacial bone-like hydroxyapatite layer when the bioglass was put in contact with biological fluids in vivo. Among a number of tested compositions, the one exhibiting the highest bioactivity index is the well-known trademarked 45S5 Bioglass®. The topic received increasing attention particularly after 1985 when this material entered in the market of biomedical devices, inspiring many other investigations aiming at further exploring the in vitro and in vivo performances of this BG, or developing other related BG compositions. The research efforts gradually revealed a number of shortcomings of 45S5 Bioglass®, mostly derived from its high sodium content, initially intended to decrease the melting temperature and accelerating the degradation of the silicate network over time. But the extensive release of sodium from 45S5 Bioglass® in the biological fluids creates a high pH cytotoxic environment. Other serious drawbacks include a fast degradation rate, and a poor sintering ability, which hinders the reliable fabrication of porous scaffolds. Therefore, sol-gel was regarded as an attractive alternative to prepare alkali-free BG compositions. The process uses inorganic and/or organic precursors, which undergo hydrolysis and condensation at room-temperature, being less costly. When properly conducted, the sol-gel process might result in amorphous structures with all the components intimately mixed at the atomic scale. Moreover, developing new better performing materials for bone tissue engineering is a growing concern, as the ageing of the world’s population leads to lower bone density and osteoporosis. This work describes the sol-gel synthesis of a novel quaternary silicate-based BG with the composition 60 SiO2 – 34 CaO – 4 MgO – 2 P2O5 (mol%) was prepared using acidified distilled water as single solvent. By controlling the kinetics of the hydrolysis and condensation steps, an amorphous glass structure could be obtained. The results of XRD of samples calcined within the temperature range from 600-900 ºC demonstrated that amorphous nature was maintained until 800 ºC, followed by partial crystallization at 900 ºC. The specific surface area, an important factor in osteoconduction, was also evaluated over different temperatures, ranging from 160.6 ± 0.8 m2/g at 600 ºC down to 2.2 ± 0.1 m2/g at 900 ºC, being accompanied consistent changes in average pore size and agreeing pore size distribution. The immersion of the BG particles in simulated body fluid (SBF) led to the formation of an extensive apatite layer on its surface. These overall results indicate the proposed material is very promising for biomedical applications in bone regeneration and tissue engineering.

The influence of a high inclusion level of Chlorella vulgaris, individually and supplemented with two carbohydrase mixtures, in finishing pig diets was assessed on zootechnical performance, carcass characteristics, pork quality traits and nutritional value of pork fat. Forty crossbred entire male pigs, sons of Large White × Landrace sows crossed with Pietrain boars, with an initial live weight of 59.1 ± 5.69 kg were used in this trial. Swines were randomly assigned to one of four dietary treatments (n=10): cereal and soybean meal-based diet (control), control diet with 5% C. vulgaris (CV), CV diet supplemented with 0.005% Rovabio® Excel AP (CV+R) and CV diet supplemented with 0.01% of a four-CAZyme mixture (CV+M). Animals were slaughtered, after the finishing period, with a BW of 101 ± 1.9 kg. Growth performance, carcass characteristics and meat quality traits were not influenced (p > 0.05) by the incorporation of C. vulgaris in the diets. However, the inclusion of the microalga in finishing pig diets increased some lipid-soluble antioxidant pigments and n-3 PUFA, and decreased the n-6:n-3 ratio of fatty acids, thus ameliorating the nutritional value of pork fat. Moreover, the supplementation of diets with the carbohydrase mixtures did not change (p > 0.05) neither animal performance nor meat quality traits, indicating their inefficacy in the increase of digestive utilization of C. vulgaris by pigs under these experimental conditions. It is concluded that the use of C. vulgaris in finishing pig diets, at this high incorporation level, improves the nutritional value of pork fat without compromising pig performance.

The daily path of the Sun across longitude yields night and day, but the Sun also travels across latitude on a belt 47° wide. The Sun meridian declination explains the annual budget of natural beam irradiance (NBI), which is the irradiance delivered to the Earth’s surface as a normal projec-tion from the Sun. Data for the sun meridian declination data were obtained from the geometric model. The distribution of NBI was weighed between the Tropics of Cancer and Capricorn. The variation patterns of the solar declination conform to the dynamics of pendular motion. The joint distributions of velocity or acceleration of meridian declination against declination fit circular graphs. The NBI budget fluctuates in inverse proportion to the velocity of declination, yielding 18 sun-paths per degree for latitudes above 20°, and 6 sun-paths per degree for latitudes under 20°. All sites of the planet, whose latitude coincide, whether within or between hemispheres, accumu-late an equivalent budget of NBI.

This paper analyses the application of deep learning techniques for predicting wave overtopping events in port environments using sea state and weather forecasts as inputs. The study was conducted in the outer port of Punta Langosteira, A Coruña, Spain. A video recording infrastructure was installed to monitor overtopping events from 2015 to 2022, identifying 3709 overtopping events. The data collected was merged with actual and predicted data for the sea state and weather conditions during the overtopping events, creating three datasets. We used these datasets to create several machine learning models to predict whether an overtopping event would occur based on sea state and weather conditions. The final models achieved a high accuracy level during the training and testing stages: 0.81, 0.73, and 0.84 average accuracy during training and 0.67, 0.48, and 0.86 average accuracy during testing, respectively. The results of this study have significant implications for port safety and efficiency, as wave overtopping events can cause disruptions and potential damage. Using deep learning techniques for overtopping prediction can help port managers take preventative measures and optimize operations, ultimately improving safety and helping to minimize the economic impact that overtopping events have on the port's activities.

Pressure ulcers carry a significant risk in clinical practice and require effective preventive measures. This paper proposes a practical and interpretable approach to estimate the risk levels of pressure ulcers using decision tree models. In order to address the common problem of imbalanced learning in nursing classification datasets, various oversampling configurations are analyzed to improve data quality prior to modeling. The decision trees built are based on three easily identifiable and clinically relevant pressure ulcer risk indicators: mobility, activity and skin moisture. Their analysis allows nursing professionals to predict the risk levels of pressure ulcer and make informed decisions about patient care. Additionally, this research introduces a novel tabular visualization method to enhance the usability of the decision trees in clinical practice. The approach proposed aims to support nursing professionals in making timely decisions regarding the appropriate preventive interventions according to the risk levels of pressure ulcers, thus improving patient outcomes and healthcare costs. The usefulness and effectiveness of the models presented make them a valuable resource for nursing care in the prevention of pressure ulcers.

From the linear Nash-Green fluctuations of background metric, we present the perturbation equations in an embedded four space-time. In the context of a five-dimensional bulk, we show that the perturbations are only propagated by the gravitational tensorial field equation. In a Newtonian conformal gauge, we study the matter density evolution in sub-horizon regime and on how such scale may be affected by the extrinsic curvature. We use the "extended Gold 2018'' growth dataset with 25 datapoints and the best fit Planck2018/LambdaCDM parameters. Hence, we determine the evolution equation for the density growth delta(a) as a result from the embedded equations of the background geometry. By using solar constraints, we analyse the evolution of the effective Newtonian constant G_eff and showing that applying Taylor expansion to G_eff (a) under the constraint of time-derivative of G_eff(0)=G at a= 1 in matter domination era, we get an agreement with Big Bang Nucleosynthesis (BBN) and also an alleviation of the 3-sigma tension to 1-sigma contour between (sigma8-Omega_m) of the observations from Cosmic Microwave Background (CMB) and Large Scale Structure (LSS) probes.

The application of optimization techniques to improve the performance of polymer processing technologies is of great practical consequence, since it may result in significant savings of materials and energy resources, assist recycling schemes and generate products with better properties. The present review aims at identifying and discussing the most important characteristics of polymer processing optimization problems in terms of the nature of the objective function, optimization algorithm, and process modelling approach that is used to evaluate the solutions and the parameters to optimize. Taking into account the research efforts developed so far, it is shown that several optimization methodologies can be applied to polymer processing with good results, without demanding important computational requirements. Also, within the field of artificial intelligence, several approaches can be reach significant success. The first part of this review demonstrated the advantages of the optimization approach in polymer processing, discussed some concepts on multi-objective optimization and reported the application of optimization methodologies in single and twin screw extruders, extrusion dies and calibrators. This second part focus on injection molding, blow molding and thermoforming technologies.

Given the global economic and societal importance of the polymer industry, the continuous search for improvements in the various processing techniques is of practical primordial importance. This review evaluates the application of optimization methodologies to the main polymer processing operations. The most important characteristics related with the usage of optimization techniques, such as the nature of the objective function, the type of optimization algorithm, the modelling approach used to evaluate the solutions, and the parameters to optimize, are discussed. The aim is to identify the most important features of an optimization system for polymer processing problems, and define the best procedure for each particular practical situation. For this purpose, a state-of-the-art of the optimization methodologies usually employed is first presented, followed by an extensive review of the literature dealing with the major processing techniques, the discussion being completed by considering both the characteristics identified and the available optimization methodologies. This first part of the review focus on extrusion, namely extruders, extrusion dies and calibrators. It is concluded that there is a set of methodologies that can be confidently applied in polymer processing, with a very good performance and without the need of demanding computation requirements.

Enzymes are the most efficient catalysts known working in an aqueous environment near room temperature. The folding of individual polymer chains to functional single-chain nanoparticles (SCNPs) offers many opportunities for the development of artificial enzyme-mimic catalysts showing both high catalytic activity and specificity. In this review, we highlight recent results obtained in the use of SCNPs as bioinspired, highly-efficient nanoreactors (3–30 nm) for the synthesis of a variety of nanomaterials (inorganic nanoparticles, quantum dots, carbon nanodots), polymers and chemical compounds, as well as nanocontainers for CO₂ capture and release.

Objectives: To assess the short-term impact of a single global stretching session on plantar pressures and lumbar range of motion (RoM) over one week in sedentary university students. Design: A randomised controlled trial with two parallel groups. Participants: Sixty-four university students were randomly assigned to a stretching group or control group. The stretching group received a single session of global stretching and the control group remained seated for the same length of time as the stretching session. Main outcome measures: Lumbar RoM and plantar pressures were assessed before, immediately after, 48 hours after, and 7 days after intervention. Results: Group-by-time interaction was significant for lumbar lateral flexion (p = 0.044), right maximal pressure (p = 0.003), left maximal pressure (p = 0.008), right mean pressure (p = 0.025), left mean pressure (p = 0.002), and maximal pressure minus mean pressure in right foot (p = 0.007). The model with plantar pressures showed a significant difference for group-by-time interaction (p = 0.010).Conclusion: Global stretching seems to counteract the ill-effects of prolonged sitting up to seven days with respect to plantar pressure in standing without improving lumbar ROM

ABSTRACT(1) Background:. Because of the numerous debates about the training on the use of force provided to police officers, this study intends to evaluate several parameters (Police Ergonomic Parameters, PEP) in connection with such training. (2) Research method: : A smartsuit equipped with a set of 19 wireless sensors including triaxial accelerometers, Inertial Measurement Units (IMU), gyroscopes and geomagnetic sensors has been used. Biomechanics of Body (BoB) software application allowed to evaluate the risks associated to the basic technique number 1 of the Operational Tactical Procedures (OTP) with regard to the established parameters (PEP). The OTP basic technique number 1 was performed by 4 novice police officers. (3) Results: According to the evaluation of a number of specific parameters such as Rapid Entire Body Assessment (REBA), asymmetry over the sagittal plane, compression force at the L5-pelvic junction, shear force at the L5-pelvic junction and total muscle power, it was observed that the measured values clearly varied depending on each individual's performance, although they remained consistent with the values established by Police Ergonomic Parameters, and were significantly different from the values measured when a police officer used a traditional physical intervention procedure, in which case, the values measured were indicative of higher risks. (4) Conclusions: In order to achieve lower and more uniform values in terms of risk, we believe that it is necessary to employ a greater number of hours to the training of police officers on the use of force and also the convenience of conducting further studies on a larger and more representative sample of officers.

In this paper, we present a new parametric class of optimal fourth-order iterative methods to estimate the solutions of nonlinear equations. After the convergence analysis, we study the stability of this class by using the tools of complex discrete dynamics. This allows us to select those elements of the class with lower dependence on initial estimations. We verify by means of numerical tests that the stable members on quadratic polynomials perform better than the unstable ones, when applied to other non-polynomial functions. We also compare the performance of the best elements of the family with known methods, such as the schemes by Newton or Chun, among others, showing robust and stable behaviour.

The study´s goals were to determine the health status of a group of heart transplant recipients (HTR) and their level of physical activity and to compare the health status among them and with a group of healthy sedentary individuals. Fifty-four HTR and eighteen S were assigned to four groups, according to their level of physical activity (determined with The International Physical Activity Questionnaire); patients with a low, a moderate and a high level of physical activity (HTRL, HTRM and HTRH, respectively) and sedentary individuals (S). Participants underwent a basic blood analysis and several tests to assess their cardiovascular, neuromuscular, functional mobility condition and their quality of life. The S and HTRH were very similar in terms of BP, HR and blood analysis while HTRM and HTRL differed from both S and HTRH in these parameters. Regarding the cardiovascular, neuromuscular, functional mobility, and quality of life variables assessed in this study, HTRH showed the best results across all of them, followed by S, HTRM, and HTRL. It is suggested that the weekly level of physical activity of HTR should be high, what might help them to enhance their health and quality of life.

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

Clean use of photons from light to activate chemical reactions offer many possibilities in different fields, from chemistry and biology to materials science and medicine. This review article describes the advances carried out in last decades toward the phototriggered synthesis of single-chain polymer nanoparticles (SCNPs) as soft nanomaterials with promising applications in enzyme-mimicking catalysis and nanomedicine, among other different uses. First, we summarize different strategies developed to synthesize SCNPs based on photoactivated intrachain homocoupling, phototriggered intrachain heterocoupling and photogenerated collapse induced by external cross-linker. Next, we comprehensively review the emergent topic of photoactivated multifolding applied to SCNP construction. Finally, we conclude by summarizing recent strategies towards phototriggered disassembly of SCNPs.

Fluorophore molecules can be monitored by fluorescence spectroscopy and microscopy which are highly useful and widely used techniques in cell biology, biochemistry and medicine (e.g., biomarker analysis, immunoassays, cancer diagnosis). Several fluorescent micro- and nanoparticle systems based on block copolymer micelles and cross-linked polymer networks, quantum dots, -conjugated polymers, and dendrimers have been evaluated as optical imaging systems. In this review, we highlight recent advances in the construction of fluorescent single-chain nanoparticles (SCNPs) which are valuable artificial soft nano-objects with tunable, small size (as small as 3 nm). In particular, the main methods currently available to endow SCNPs with fluorescent properties are discussed in detail, showing illustrative examples.

The self-assembly is an intriguing process of great importance in general soft matter and thus re-ceives an ever-growing scientific interest. Its most trivial example is the entropy-driven crystalli-zation of hard spheres. Past works have established the similarities and differences in the phase behavior of monomers and chains made of hard spheres. In the present work, inspired by the dif-ference in the melting points of the pure components, we study, through Monte Carlo simulations, the phase behavior of athermal mixtures composed of fully flexible polymers and individual monomers of uniform size. We analyze how the relative number fraction and the packing density affect crystallization and the established ordered morphologies. A synergetic effect is observed in the crystallization leading to synchronous crystallization of the two species. Structural analysis of the resulting ordered morphologies shows perfect mixing and thus no phase separation, which could split the system into polymer-rich and monomer-rich domains. Due to the constraints imposed by chain connectivity, the local environment of the individual spheres is systematically more spherical and more symmetric compared to the one of spheres belonging to chains. In general, increasing polymer content leads to reduction of the degree of crystallinity. According to the present findings, relative concentration is another determining factor to control the phase behavior of hard colloidal systems based on polymers.

Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. Here we present a new methodology combining satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, applied within slope unit polygons. We studied a former mining area in southeast Spain, and the method proved useful in detecting and characterizing a considerably large number of unstable slopes. Out of 1,959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through the validation analysis (2.5 cm/year). Eventually, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear and easily comparable information to analyze slope instabilities in different settings, not limited to mining areas.

Polyalcohol liquefaction can be done by acid or basic catalysis producing polyols with different properties. This study compared the mechanical properties of foams produced using polyols from liquefied Cytisus scoparius obtained by acid and basic catalysis and using two different foam catalysts. The differences were monitored using FTIR analysis. Acid-catalyzed liquefaction yielded 95.1 %, with the resultant polyol having an OH index of 1081 mg KOH/g while basic catalysis yielded 82.5 %, with a similar OH index of 1070 mg KOH/g. Generally, compressive strength with dibutyltin dilaurate (DBTDL) ranged from 16 - 31 kPa (acid-liquefied polyol) and 12 -21 kPa (base-liquefied polyol), while with stannous octoate (TIN), it ranged from 17 - 42 kPa (acid) and 29 - 68 kPa (base). Increasing water content generally decreased the compressive modulus and strength of foams. Higher water content led to a higher absorption at 1670 cm-1 in the FTIR spectrum due to the formation of urea. Higher isocyanate indices generally improved compressive strength, but high amounts led to unreacted isocyanate that could be seen by a higher absorption at 2265 cm-1 and 3290 cm-1. DBTL was shown to be the best foam catalyst due to higher trimer conversion seen in the spectra by a higher absorption at 1410 cm-1. Acid and base-derived polyols lead to different polyurethane foams with different FTIR spectra, particularly with a higher absorption at 1670 cm-1 for foams from acid-derived liquefaction.

The high sensitivity of chiroptical responses to conformational changes and supramolecular interactions has prompted an increasing interest in the development of chiroptical applications. However, prediction and understanding the chiroptical responses of the necessary large systems may not be affordable for calculations at high levels of theory. In order to facilitate the development of chiroptical applications, methodologies capable of evaluating the chiroptical responses of large systems are necessary. Exciton chirality method has been extensively used for the interaction between two independent chromophores through the Davydov model. For systems presenting C2 or D2 symmetry one can get to the same results by applying the selection rules. In the present article, analysis of the selection rules for systems with symmetries Cn and Dn with n = 3 and 4 is used to uncover the origin of their chiroptical responses. We hope that the use of the chiroptical symmetry analysis (CSA) for systems presenting the symmetries explored herein as well as for systems presenting higher symmetries will serve as a useful tool for the development of chiroptical applications.

This review explores the potential of microalgae as a sustainable and nutritionally rich alternative for mineral supplementation in poultry diets, addressing both the opportunities and challenges in this emerging field. Poultry nutrition, pivotal to the health and productivity of birds, traditionally relies on inorganic and organic mineral sources, which, while effective, raise environmental and economic concerns. Microalgae offer a promising solution with their high content of essential minerals, proteins, vitamins, and bioactive compounds. The review delves into the nutritional profile of various microalgae, highlighting their rich mineral content, crucial for physiological processes in poultry. It examines the bioavailability of these minerals and their impact on poultry health and productivity. Furthermore, it evaluates the environmental sustainability of microalgae cultivation and acknowledges the challenges in using microalgae in poultry diets, particularly in terms of the economic viability of large-scale production and the consistency of nutrient composition. It discusses the importance of rigorous safety assessments and regulatory compliance, given the potential risks of toxins and heavy metals. Overall, this analysis aims to provide a clear understanding of the role microalgae could play in poultry nutrition and address sustainability challenges in animal agriculture, while also considering future perspectives and advancements needed in this field.

The majority of structures supporting solar panels are founded on thin-walled metal piles driven into the ground to optimize costs and construction timelines. These pile foundations are subjected to repetitive lateral loads from various external forces, such as wind, which can compromise the in-tegrity of the pile-soil system. Given that the proper functioning of photovoltaic solar plants is typically expected for 20-30 years, predicting their useful life under fatigue loading becomes crucial. This research investigates the lateral load response of a single pile subjected to different fatigue loads in stiff cohesive soils. Additionally, the effect of loading cycles on the degradation of pile-soil ad-hesion is studied through pull-out field tests. This study reveals that soil fatigue does not occur under repetitive loading, and the soil’s stiffness remains constant once the cycles causing soil compaction have been overcome. Nevertheless, the soil's accumulated plastic deflection steadily increases once soil compaction due to cyclic loading occurs. The implications of these results on the fatigue life of photovoltaic solar panel foundations are discussed.

The high transmissibility, rapid evolution, and immune escape of SARS-CoV-2 variants can influence the course of infection and, in turn, morbidity and mortality in COVID-19, posing a challenge in controlling transmission rates and contributing to the emergence and spread of new variants. The factors that shape viral genetic variation are consequently essential for understanding the evolution and transmission of SARS-CoV-2, especially in vaccinated individuals where immune response plays a role in the progression and spread of this disease. This study assessed. In this context, we evaluated the impact of immunity induced by the CoronaVac vaccine (Butantan/Sinovac) on intra-host genetic diversity, analyzing 118 whole-genome sequences of SARS-CoV-2 from unvaccinated and vaccinated patients infected with the Gamma variant. Vaccination with CoronaVac favors negative selection at the intra-host level in different genomic regions and prevent greater genetic diversity of SARS-CoV-2, which may help reduce the emergence of new mutations, reinforcing the importance of vaccination in reducing virus transmission.

The thermomechanical and viscoelastic properties of a glass fiber polyethylene terephthalate glycol (GF/PETG) continuous unidirectional (UD) tape were investigated using differential scanning calorimetry (DSC), thermo-mechanical analysis (TMA), and dynamic mechanical analysis (DMA). The study identified five operational conditions based on Army Regulation 70-38 Standard. The DSC results revealed a glass transition temperature of 78.0 ± 0.3°C, guiding the selection of temperatures for TMA and DMA tests. TMA provided the coefficient of thermal expansion in three principal directions, consistent with known values for PETG and GF materials. DMA tests, including strain sweep, temperature ramp, frequency sweep, creep, and stress relaxation, defined the linear viscoelastic region and temperature-dependent properties of the material. The frequency sweep indicated an increase in modulus with rising frequency, identifying several natural frequency modes. Creep and stress relaxation tests showed time-dependent behavior, with strain increasing under higher loads and stress decreasing over time for all tested input values. Viscoelastic models fitted to the data yielded R² values of 0.99, demonstrating good agreement. The study successfully measured thermo-mechanical and viscoelastic properties across various conditions, providing insights into how temperature influences the material's mechanical response under extreme conditions.

In arid and semi-arid regions, groundwater is often the only available source of water. However, overexploitation and pollution have led to a decrease in both the quantity and quality of ground-water. Therefore, proper management of groundwater resources is essential to promote sustainable development. Numerical simulation has emerged as a valuable tool to address these challenges due to its ability to accurately and efficiently model groundwater systems. This systematic review aims to evaluate the current knowledge on the use of numerical groundwater flow models for planning and water resources management in Latin American countries. A total of 166 research articles published between years 2000 and 2024. We analyzed, summarizing details as: the study regions, numerical simulation methods and software, performance metrics, modeling units, modeling limitations, and prediction scenarios. In addition, we discuss alternatives to address the constraints and difficulties and suggests recommendations for future research. Continued research, improvement and de-velopment of numerical groundwater models is essential to ensure the sustainability of groundwater resources.

Topic discovery is finding the main idea of large amounts of textual data. It indicates the recurring topics in the documents, allowing an overview of the texts. Current topic discovery models receive the texts, with or without pre-processing of Natural Language Processing. The processing consists of stopwords removal, text cleaning and normalization (lowercase conversion). A topic discovery model that receives texts with or without processing generates general topics since the input data is many uncategorized texts. The general topics do not offer a detailed overview of the input texts, and manual text categorization is a time-consuming and tedious task. Accordingly, it is necessary to integrate an automatic text classification task in the topic discovery process to obtain specific topics with their top words that contain relevant relationships based on belonging to a class. Text classification performs a word analysis that makes up a document to decide what class or category is being identified; then, integrating the text classification before a topic discovery process will provide latent topics depicted by top words with a high coherence in each topic based on the previously obtained classes. Therefore, this paper exposes a approach that integrates text classification into topic discovery from large amounts of English textual data, such as 20-Newsgroup and Reuters corpora. The text classification is accomplished with a Convolutional Neural Network(CNN) incorporating three embedding models based on semantic relationships. The topic discovery over categorized texts is realized with Latent Dirichlet Analysis(LDA), Probabilistic Latent Semantic Analysis(PLSA), and Latent Semantic Analysis(LSA) algorithms. An evaluation process was performed based on the normalized topic coherence metric. The 20-Newsgroup corpus was classified, and twenty topics with ten top words were discovered for each class, obtaining 0.1723 normalized topic coherence when applying LDA, 0.1622 with LSA, and 0.1716 with PLSA. The Reuters corpus was also classified, obtaining 0.1441 normalized topic coherence when applying the LDA algorithm to obtain 20 topics for each class.

Embedding representation models characterize each word as a vector of numbers with a fixed length. These models have been used in tasks involving text classification, such as recommen- dation and question-answer systems. Semantic relationships are words with a relationship between them providing a complete idea to a text. Therefore, it is hypothesized that an embedding model involving semantic relationships will provide better performance for tasks that use them. This paper presents three embedding models based on semantic relations extracted fromWikipedia to classify texts. The synonym, hyponym, and hyperonym semantic relationships were the ones considered in this work since previous experiments have shown that they are the ones that provide the most semantic knowledge. Lexical-syntactic patterns present in the literature were implemented and subsequently applied to the Wikipedia corpus to obtain the semantic relationships present in it. Several semantic relationships are used in different models: synonymy, hyponym-hyperonym, and a combination of the first two. A convolutional neural network was trained for text classification to evaluate the performance of each model. The results obtained were evaluated with the metrics of precision, accuracy, recall, and F1-measure. The best values obtained with the second model were accuracy of 0.79 for the 20-Newsgroup corpus. F1-measure and recall of 0.87 respectively for the Reuters corpus.

The vibrational excitation cross section of a diatomic molecule by positron impact is obtained using wavepacket propagation techniques. The dynamics was carried on a two-dimensional potential energy surface which couples a hydrogen-like harmonic oscillator to a positron via a spherically symmetric correlation polarization potential. The cross section for the excitation of the first vibrational mode is in good agreement with previous reports. Our model suggests that a positron couples to the target vibration by responding instantly to an interaction potential which depends on the target vibrational coordinate.

Piperine, an active plant alkaloid from black pepper (Piper nigrum), has several pharmacological effects: antioxidant, anti-inflammatory and immunomodulatory, which involves inhibiting molec-ular events associated with various stages of cancer development. The aim of this study was to investigate the molecular mechanisms of action of piperine in relation to its potential anticancer effect on head and neck cancer cells. Parameters related to neoplastic potential, analysis of cyto-kine, protein and gene expression were investigated in the head and neck cancer cell lines (HEp-2 and SCC-25) treated with piperine. The results of the tests indicated that piperine modified mor-phology, inhibited viability and the formation of cell colonies. Piperine promoted genotoxicity by triggering apoptosis and cell cycle arrest in G2/M and S. A decrease in cell migration was also observed, and decreased expression of MMP2/9 genes. Piperine also reduced the expression of inflammatory molecules (PTGS2 and PTGER4), regulated the secretion of cytokines (IF-y and IL-8) and modulated the expression of ERK and p38. These results suggest that piperine exerts anti-cancer effects on tumor cells, and could be a promising natural treatment by regulating signaling pathways associated with head and neck cancer.

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

The rapid technological progress has ushered in a new era of human-computer interaction, where the distinction between the physical and virtual realms is becoming increasingly blurred. This research paper explores the profound and multifaceted intersection of Human-Data Interaction (HDI) and Data Virtualization (DV), examining how emerging technologies can significantly enhance the exploration, comprehension, and utilization of complex, multidimensional data sets. Informed by the insights gleaned from prior research in this domain , the present study delves into the potential of DV techniques to improve HDI, with a particular focus on three experimental investigations conducted within the realms of education, healthcare, and retail. The findings reveal the benefits and potential challenges associated with the implementation of DV in these diverse contexts, offering valuable guidance for the design and development of future HDI systems. Drawing upon a diverse array of authoritative sources, this paper presents a holistic, forward-looking perspective on the future of HDI, underscoring the critical role that DV will play in shaping the next generation of human-computer interfaces and facilitating a deeper, more intuitive understanding of the digital world. Furthermore, the paper presents a preliminary framework for integrating HDI principles into standard design practices. This framework outlines key considerations and guidelines to help designers and developers incorporate HDI techniques more effectively into the development of data-driven applications and interfaces.The proposed framework outlines key considerations for enhancing data accessibility and comprehension, empowering users to exercise greater control over their data, and cultivating transparent dialogues between data providers and end-users. By establishing this conceptual foundation, the paper aims to facilitate the seamless integration of HDI principles into standard design practices, ultimately leading to more intuitive, user-centric, and ethically-grounded approaches to data interaction and utilization.

Background: The study demonstrates the sustainable synthesis of translucent zinc oxide (ZnO) nanowires using Moringa seed extract, highlighting eco-friendly and sustainable approaches. Methods: Characterization techniques such as X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) confirmed the formation of ZnO nanostructures with diverse morphologies, including nanowires and spherical clusters. Results: The synthesized ZnO nanowires exhibited remarkable photocatalytic activity, achieving over 89% degradation efficiency of methylene blue (MB) under UV light within 80 minutes, demonstrating their potential for wastewater treatment applications. Conclusions: The research findings support Sustainable Development Goals (SDGs) related to clean water, climate action, and life below water and on land, highlighting the role of eco-friendly nanostructures in environmental remediation. The dual advantage of Moringa seed extract, providing both a sustainable synthesis route and health benefits due to its rich content of vitamins and phytochemicals, underscores the potential of integrating natural resources in nanotechnology for environmental and health applications.

Polycystic ovary syndrome (PCOS) is a prevalent condition characterized by manifestations that can influence self-image and potentially result in psychological distress; however, data from literature on sexual function (SF) in PCOS women are contradictory. We aimed to evaluate sexual dysfunction (SD) in PCOS women by carrying out a systematic review and meta-analysis, using the gold-standard assessment tool SD-diagnosis (Female Sexual Function Index:FSFI). Seven databases were analyzed until August-2023; study quality was assessed by risk of bias and Newcastle Ottawa Scale. Our analysis encompassed 25 case-control studies (9933 women). PCOS group presented significantly lower scores in arousal (MD= -0.36 CI95%-0.60;-0.11), lubrication (MD= -0.52 CI95%-0.75;-0.28), orgasm (MD= -0.39 CI95%-0.57;-0.20), satisfaction (MD= -0.32 CI95%-0.50;-0.14) and pain subdomains (MD= -0.46 CI95%-0.75;-0.16), as in overall FSFI score (MD= -2.27 CI95%-3.23;-1.31). Overweight/obese (OW/O) patients exhibited significantly higher overall FSFI than OW/O controls (MD=1.98 CI95%0.68;3.27), particularly in lubrication (MD= -0.34), orgasm (MD= -0.26) and satisfaction (MD= -0.25) subdomains. These findings offer insights regarding SD in PCOS women and emphasize the need to incorporate SF assessment into multidisciplinary care. By this way, PCOS can be also considered a gateway diagnosis to other long-term consequences. Further research should focus on controlling variables, as ethnicity, culture, religion and economic disparities.

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

Considering the concerns for emissions reduction in the maritime sector, the present paper evaluates, through modeling and simulation, the oxy-fuel combustion in a two-stroke ship engine (2SE) and the best production system configuration to obtain the required oxygen (O2). An initial model of a ship engine is calibrated with the engine manufacturer’s data, and then adapted to work with O2 as the oxidant to eliminate nitrogen oxides (NOx) emissions and with exhaust gas recirculation (EGR) to control the in-cylinder combustion temperature. Mixed Ionic-Electronic Conducting (MIEC) membranes produce the necessary O2 from the ambient air, which is heated up and pressurized by a heat exchanger and turbocharging coupled system to provide the air conditions required for the proper operation of the MIEC. Several layouts of this system are evaluated for the full load engine operating point to find the optimum O2 production system configuration. Results reveal that the engine operating under oxy-fuel combustion conditions avoids NOx emissions at the expense of higher brake specific fuel consumption (BSFC) to obtain the original brake torque, and also expels a stream composed exclusively of CO2 and H2O, what facilitates the separation of CO2 from exhaust gases.

Melt mixing is a convenient method to prepare polymer nanocomposites, but the extent of the dispersion of the solid filler reached is often limited, and may compromise the anticipated performance of these materials during service. Since the efficiency of extensional flows on dispersion is now well recognized, several mixers were designed with the aim of inducing both shear and extensional flow components. This work combines experimental and numerical data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with equal outer diameter and alternating larger and smaller inner diameters, thus creating a series of converging/diverging flows. Numerical simulation of the flow using the opensource OpenFOAM software assuming both inelastic and viscoelastic responses predicted the velocity, streamlines, flow type and shear and normal stress fields for the mixer. Experimental and computed data were combined to determine the trade-off between the local degree of dispersion of the PP/GnP nanocomposite, measured as Area ratio, and the absolute average value of the hydrodynamic stresses multiplied by the local cumulative residence time. From considerations based on a theoretical approach to dispersion, the cohesive strength of the GnP agglomerates studied was estimated to be in the range 3 - 10kPa.

Steel slag is a co-product of the steelmaking industry, this material is rarely used as a binder due to its low cementitious properties. Thus, it´s believed that the alkaline activation of steel slag can enable its use as a cementitious material. This work has the objective of making a systematic bibliographic review on the theme "slag melt as a precursor in activated alkali binders". To this end, the ProKnow-C method was used for the selection and analysis of relevant research on the topic. The portfolio resulted in 71 texts, mostly journals paper. Bibliometrics showed that the country with the most publications is China and the journal with the most publications is Construction and Building Materials. The critical analysis concluded that the XRD, XRF, and compressive strength tests are the most used for the characterization of the material. It is possible to establish that there are some knowledge gaps on the subject, such as better mechanical characterization and greater production of works with dosing by the one-part method.

The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective was to determine the flight pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study's lag; the lower the height, the greater the percentage of CBBs captured. In Experiments A and B, the traps placed at 0.5m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5m above the ground in the multi-level CT showed a higher capture percentage than the individually placed trap (also at 1.5m). The pattern of the capture and proportion of the CBB in the CTs were maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggested that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

Combining antiviral drugs with different mechanisms of action can help prevent the development of resistance by attacking the infectious agent through multiple pathways. Additionally, by using faster and more economical screening methods, effective synergistic drug candidates can be rapidly identified, facilitating faster paths to clinical testing. In this work, a rapid method was standardized to identify possible synergisms from drug combinations. We analyzed the possible reduction of antiviral effective concentration of drugs already approved by the FDA, such as ivermectin  (IVM), ribavirin (RIBA) and acyclovir (ACV) against Zika virus (ZIKV), Chikungunya virus (CHIKV) and herpes virus type 2 (HHV-2). Essential oils (EOs) were also included in the study since they have been reported for more than a couple of decades to have broad-spectrum antiviral activity. We also continued studying the antiviral properties of one of our patented molecule with broad-spectrum antiviral activity, the ferruginol analogue 18-(phthalimid-2-yl)ferruginol (phthFGL). In general, the combination of IVM, phthFGL and Oregano EO showed the greatest synergism potential against CHIKV, ZIKV and HHV-2, obtaining a reduction in the EC99 value of up to ~8, and ~27, and ~12-fold for CHIKV, in example, respectively. The ternary combination RIBA, phthFGL, Oregano EO was slightly more efficient than the binary combination RIBA/phthFGL but much less efficient than IVM, phthFGL, Oregano EO which indicates that IVM could contribute more to the differentiations of cell targets (for example by inhibition of host heterodimeric importin IMP α/β1 complex) than ribavirin. PhthFGL showed a good pharmacokinetic profile.

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

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

The use of principal components analysis provided information about the main characteristics of teams, based on a set of indicators, instead of displaying individualized information for each of these indicators. In this work we have considered reducing an extensive data matrix to improve interpretation, using the principal components analysis. Subsequently, with new components and with a multiple linear regression, we have carried out a comparative analysis between the best and bottom teams of LaLiga. The sample consisted of the matches corresponding to the 2015/16, 2016/17 and 2017/18 seasons. The results showed that the best teams were characterized and differentiated from bottom teams in the realization of a greater number of successful passes and in the execution of a greater number of dynamic offensive transitions. The bottom teams were characterized by executing more defensive than offensive actions and showing a fewer number of goals, a greater ball possession time in the final third of the field. Goals, ball possession time in the final third of the field, number of effective shots and crosses are the main performance factors that influence the offensive success of football. This information allows us to increase knowledge about the key performance indicators in football.

The aim of this study was to identify gender differences in technical-tactical behaviour in football. To this end 68 matches of the first division of the Spanish men’s and women´s league, corresponding to 2016/17 season were analyzed. A comparison of medians was carried out using the Mann-Whitney U-test were conducted as post hoc test and a grouping of the variables through the clustering bootstrapping technique in both groups. We have detected statistically significant differences regarding all accurate passes, in favour of men, as well as a greater number of yellow cards. In female football, a greater number of picking up free balls, interceptions, lost balls, recoveries, challenges and attacks, both positional and counterattacks, are produced. The clustering analysis also allowed that in male football, the circumstance of receiving a red card is closely related to the number of goals conceded and most of the shots on goal are achieved by positional attacks. In women's football, ball possession on own half is closely related to the number of losses. These results could be useful for gender-specific training information for optimal preparation. However, more research is warranted to establish the main gender differences and characterize women's football.

Right atrial isomerism (RAI) is a complex entity whose treatment and outcome are heterogeneous. The aim of this study was to analyze the results obtained after cardiac surgery in patients with RAI. A retrospective study was conducted; it included patients diagnosed with RAI who underwent cardiac surgery; their follow-up was from January 1, 2010 to March 31, 2020. Demographic characteristics and perioperative conditions were described. Thirty-eight patients with RAI were included, the median age was 4 years (IQR 2-9.2), and 57.9% were men. The main diagnoses were atrioventricular canal (63.2%) and pulmonary stenosis (55.3%). The most common surgical procedures were modified Blalock‐Taussig shunt (65.8%) and total cavopulmonary connection with an extracardiac conduit fenestrated without cardiopulmonary bypass (15.9%). The use of inhaled nitric oxide was a marker of postoperative mortality in critically ill patients (OR: 10.33; 95% CI: 1.04 - 102.08; p = 0.02). The overall survival was 86.8%, with a better outcome in those who did not require reintubation (Log Rank, p < 0.01). The survival of RAI was similar to other centers of reference. Individuals with RAI should be evaluated rigorously to determine an adequate repair strategy, considering high morbidity and mortality.

Objective: To provide mechanistic evidence for the epidemiological link between long-term use of alcohol containing mouthwashes and oral cancer.Methods: Human epithelial keratinocytes were exposed for 30 seconds to concentrations of ethanol commonly present in mouthwashes. After a recovery period, cell viability was assessed with the MTT assay.Results: A marked cytotoxic effect was observed for ethanol concentrations of 20% and above. Conclusions: The cytotoxicity of ethanol can explain the epidemiological association between mouthwash use and oral cancer. Recent findings indicate that the risk of developing cancer in a tissue is strongly determined by the number of stem cell divisions accumulated by the tissue during a person's lifetime; cell division is a major source of mutations and other cancer-promoting errors. Since cell death activates the division of stem cells, the cytotoxicity of ethanol on the cells lining the oral mucosa will promote the division of the stem cells located in deeper layers to produce new cells to regenerate the damaged epithelium. If we regularly use mouthwashes containing cytotoxic concentrations of ethanol, we will force the stem cells of the oral cavity to divide more often than usual and our risk of developing oral cancer will probably increase.Clinical significance: Many mouthwashes contain percentages of ethanol above 20%. Because ethanol is not crucial to prevent and reduce gingivitis and plaque, members of the dental team should consider the potential risk of oral cancer associated with frequent use of alcohol containing mouthwashes when advising their patients.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Abstract: Background: Surgery on varicose veins (crossectomy and stripping) leads to recurrence and has clinical and socio-economic repercussions. Their etiopathogenesis has yet to fully under-stood. Objective: Study the expression of endoglin and other molecules involved in the neovascu-larisation process in patients suffering from this disease. Methods: 43 patients that have undergone surgery for varicose veins (24 primary and 19 recurrent). They were identified on the venous wall (proximal -saphenofemoral junction- and distal), via real-time RT-PCR, and in serum, via ELISA: Endoglin (Eng), Vascular Endothelial Growth Factor (VEGF-A), its receptors 1 and 2 (VEGFR1 or FLT1), (VEGFR2 or FLK), and the Hypoxia-Inducible Factor (HIF-1A). All the patients signed a con-sent form. Results: The recurrent group recorded a higher expression of Eng, VEGF-A, VEGFR1 and VEGFR2 at the level of proximal venous wall compared to the primary group. HIF-1A did not record any differences. As regards the determination of the distal venous wall, no markers recorded differ-ences between the groups. Among the serum determinations, only sFLT1 recorded a significant drop among the patients with recurrent varicose veins. Conclusions: Patients with recurrent vari-cose veins record a higher expression of endoglin and other markers of angiogenesis in proximal veins. Endoglin in the blood (sEng) has not proven to be of any use in recurrent varicose veins.

In the present study, a multilayer high barrier thin blown film based on a polybutylene adipate terephthalate (PBAT) blend with polyhydroxyalkanoate (PHA), and composed of four layers, including a cellulose nanocrystals (CNC) barrier layer and an electrospun poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) hot-tack layer, was characterized in terms of surface roughness, surface tension, migration, mechanical and peel performance, barrier properties and disintegration rate. The results showed a material with a smooth surface. The overall migration test showed that the material was suitable for its use as a food contact layer. The addition of the CNC interlayer had a significant effect on the mechanical properties of the system, drastically reducing the elongation at break and, thus, the flexibility of the material. However, the material retained its elastic modulus and tensile strength. The CNC coating had a negative impact on the peeling strength, weakening the inherently strong interlayer adhesivity of the electrospun PHBV fibers. The multilayer had a good barrier to water vapor, and especially to oxygen, with its permeance reduced by up to a 90 % when the CNC layer was present. Finally, the monolayer blend film disintegrated in a period of less than 55 days in a laboratory-scale composting experiment, while the multilayer system disintegrated in 60 days. Overall, the multilayer system formed a fully compostable structure with great potential for use in food packaging applications.

As companies increasingly undergo digital transformation, the role of talent management pro-cesses becomes pivotal in enhancing overall organizational performance. The research addresses the significance of talent management in corporate digital transformation, examining whether variations in the digitalization of these processes can be attributed to company size. A qualitative approach was employed, utilizing a questionnaire, collecting responses from 202 organizations across diverse sectors. Findings reveal disparities in digitalization throughout the talent man-agement process, with pronounced presence in the attracting, selecting, and rewarding phases, but diminishing in deployment and development, further declining in planning. A positive cor-relation between company size and adoption of specific digital platforms was observed. Larger enterprises exhibit greater utilization of digital platforms in talent deployment and development. Moreover, corporate communication tools are consistently utilized in the rewarding phase, irre-spective of company size. These findings offer practical insights for organizations to optimize their digitalization strategies based on their scale, thereby contributing to more effective and tailored digitalization endeavors. The uniqueness of this research lies in its exploration of the in-fluence of company size on the digitalization of talent management processes and its potential to explain variations across different stages of these processes.

Molecular modeling studies were carried out at the DFT level of the adsorption of propane and propene on Ag surfaces as a model of the interaction of light hydrocarbons with Ag/ZrO2 catalysts for the catalytic combustion reaction. It was found that the most stable mode of adsorption of propene through its π system on Ag atom has energies consistent with chemisorption and generates an elongation of the C1=C2 bond, which would explain the increase in the activity of the catalysts as function of its metallic charge. The results obtained from the DFT calculations explain the different types of interaction between propene and propane with the metallic surface. The propene is chemisorbed on the Ag surface, distorting its bonds and generating its activation. This would imply that a higher metallic charge in the catalyst would increase the number of active sites in which this activation occurs, generating a higher activity. Besides, with the addition of O, the binding energy between the propene and the metal surface increased. On the other hand, the presence of a metallic surface is not enough for the activation of the propane molecule. This would explain why by increasing the amount of metal in the catalyst, the activity for the combustion of propane is practically not affected

Patient experience is key to patient-centered care and overall healthcare quality. This focus aligns with the growing trend of collaborative care, where patients actively participate in deci-sions alongside providers, leading to better outcomes. Patient experience goes beyond clinical results; it encompasses how patients feel throughout the care journey. Integrating patient per-spectives is essential for high-quality care. The study employed a multicenter, cross-sectional survey design utilizing a questionnaire-based approach. The data collection spanned two loca-tions within the Hospital Clínica Bíblica: San José, and Santa Ana, Costa Rica. The survey target-ed patients receiving treatment across the emergency department, surgery service, and inpatient department. A standardized Picker Patient Experience Questionnaire-33 (PPE-33) was adminis-tered to assess patients' overall experience with received services. A total of 390 questionnaires were analyzed. The participant demographics were as follows: 61.79% female, 56.15% aged be-tween 18 and 44, and 55.67% with undergraduate education. The hospital delivered high-quality service, with strong communication and accessibility (93.7%, 92.6%, and 94.4% positive respec-tively). Improvements are needed in patient rights education (22.7% positive), information about the patient's condition (74.3% positive), discharge instructions (36.5% and 71.4% positive for side effects and warning signs respectively) and addressing patient concerns (26.3% to 44.0%). Patients appreciated their privacy (95.2%), effective pain management (96.2%), respectful com-munication (97.0% and 94.8%), and overall respectful treatment. Satisfaction was influenced by factors like patient needs prioritization, rights communication, sociodemographic, health status, and comfort. The ward of admission had no significant impact on the experience. Enhancing pa-tient experience could boost loyalty and healthcare quality.

This work implements a stable algorithm in Field-Programmable Gate Arrays (FPGAs) for which two architectures (unrolling the loop) were developed and analyzed. The algorithm recovers sources located at the boundary separating two homogeneous media that make up a two-dimensional non-homogeneous region from measurements on the boundary of such region. The problem of recovering these sources is an ill-posed inverse problem as small errors in the measurement can produce important changes in the source location. Inverse source problems have many applications in different areas, such as engineering and medicine, making the proposed implementation important. The first architecture (mode one) allows considering different operating speeds, which is an advantage depending on whether we work with fast or slow signals. The second one (mode two) reduces resource consumption by exploiting the characteristics of the source identification algorithm, which is an advantage for multichannel problems such as inverse electrocardiography or electroencephalography. The architectures were tested on four FPGAs of the 7 Series of Xilinx: Spartan-7 xc7s100fgga484, Virtex-7 xc7v585tffg1157, Kintex-7 xc7k70tfbg484, and Artix-7 xc7a35tcpg236. The two FPGA implementations of the algorithm were validated using synthetic examples implemented in MATLAB. The results presented here can be extended to concentric spheres and complex geometries.

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

Predicting electricity prices is a very important issue in modern society, because the associated decision process under uncertainty requires accurate forecasts for the economic agents involved. In this paper, we apply the decision tree extension of Random Forests to the prediction of electricity prices in Spain, but with the novelty of modeling prices jointly with demand, with the purpose of achieving greater accuracy than with univariate response Random Forests, particularly in price prediction, as well as understanding the effect of the input variables (lagged values of price and demand, current production levels of available energy sources) on the joint of the two outputs. The results are very encouraging, providing significant increase in price prediction accuracy. Also, interesting methodological challenges appear as far as the appropriate choice of the relative weights of price and demand in the joint modeling is concerned and a new procedure to provide the importance variable ranking is proposed. The partykit (package of R software) library allowing for multivariate Random Forests has been used.

Despite the best efforts in air-purification, airborne infectious diseases do and will continue to spread due to continuous emission of bioaerosols by the host/infected person. To tackle the rapid spread of airborne infectious diseases, a shift in focus from air-purification to bioaerosol disinfection/ decontamination is urgently needed. In this work, we studied a cold plasma ionizer (CPI) and electrostatic precipitator (ESP)-coupled CPI (CPI-ESP) for disinfection and cleaning of bioaerosols. Using porcine respiratory coronavirus (PRCV) and E. coli in a testing chamber, we demonstrated that CPI coupled with ESP is an effective technology for inactivating aerosolized microorganisms and microorganisms spread on surfaces. In addition, we have demonstrated the efficiency of a CPI-ESP coupled device for disinfection of naturally occurring airborne microbials in a few indoor settings (i.e., an living room, a discussion room, a schoolroom and an office) to determine the treatment duration- and human activity-dependent efficacy. To understand the disinfection mechanism, we conduced fluorescence microscopy study to reveal different degree of bacteria cell membrane damage under CPI treatment.

In the present paper, we efficiently solve the two-body problem for extreme cases such as those with high eccentricities. The use of numerical methods, with the usual variables, cannot maintain the perihelion passage accurately. In previous articles, we have verified that this problem is treated more adequately through temporal reparametrizations related to the mean anomaly through the partition function. The biparametric family of anomalies, with an appropriate partition function, allows a systematic study of these transformations. In the present work, we consider the elliptical orbit as a meridian section of the ellipsoid of revolution, and the partition function depends on two variables raised to specific parameters. One of the variables is the mean radius of the ellipsoid at the secondary, and the other is the distance to the primary. One parameter regulates the concentration of points in the apoapsis region, and the other produces a symmetrical displacement between the polar and equatorial regions. The three most used geodesy latitude variables are also studied, resulting in one not belonging to the biparametric family. However, it is in the one introduced now, which implies an extension of the biparametric method. The results obtained by the method presented here now allow a causal interpretation of the operation of numerous reparametrizations used in the study of orbital motion.

Ebola virus disease (EVD) represents a global health threat. The etiological agents of EVD are 6 species of Orthoebolaviruses, with Orthoebolavirus zairense (EBOV) having the greatest public health and medical significance. EVD disease pathogenesis occurs as a result of broad cellular tropism of the virus, robust viral replication and a potent and dysregulated production of cytokines. In vivo, tissue macrophages are some of the earliest cells infected and contribute significantly to virus load and cytokine production. While EBOV is known to infect macrophages and to generate high titer virus in the liver, EBOV infection of liver macrophages, Kupffer cells, has not previously been examined in tissue culture or experimentally manipulated in vivo. Here, we employed primary murine Kupffer cells (KC) and an immortalized murine Kupffer cell line (ImKC) to assess EBOV-eGFP replication in liver macrophages. KCs and ImKCs were highly permissive for EBOV infection and IFN-γ polarization of these cells suppressed their permissiveness to infection. The kinetics of IFN-γ-elicited antiviral responses were examined using a biologically-contained model of EBOV infection termed EBOV ΔVP30. The antiviral activity of IFN-γ was transient, but a modest ~3-fold reduction of infection persisted for as long as 6 days post treatment. To assess the interferon stimulated gene products (ISGs) responsible for protection, the efficacy of secreted ISGs induced by IFN-γ were evaluated. Secreted ISGs blocked recombinant VSV expressing EBOV GP (rVSV/EBOV GP) infection, but failed to block EBOV ΔVP30. Our studies define new cellular tools for the study of EBOV infection that can potentially aid the development of new antiviral therapies. Furthermore, our data underscore the importance of macrophages in EVD pathogenesis and those IFN-γ-elicited ISGs that help to control EBOV infection.

Sustainable biomass production has significant potential for mitigating greenhouse gas emissions and is a promising alternative for the production of eco-friendly biofuels, biochemicals, and carbonaceous materials for biological, energetic, and environmental applications. Biomass from agroforestry and agricultural wastes is the richest natural carbon source and a sustainable option for woody biomass from a circular economic perspective. Portugal has several residues and by-products of agriculture, food processing, and forestry origin, and has a high availability of residual biomass. Portugal intends to reduce its dependence on energy imports and the use of fossil fuels, thereby increasing its economic performance while using biomass waste to produce high-value-added products. In this context, this review aims to explore the potential of agri-food wastes obtained from Portuguese industries via thermochemical conversion technologies as a promising sustainable alternative to woody biomass for the development of eco-friendly biofuels, biochemicals, and high-value carbonaceous materials and their applications. This strategy based on the circular bioeconomy concept can contribute to reducing the dependence on fossil fuels and minimising greenhouse gas emissions while meeting the demands of the growing population and providing a sustainable waste management solution.

In this paper, we investigate the Green measure for a class of non-Gaussian processes in $\mathbb{R}^{d}$. These measures are associated with the family of generalized grey Brownian motions $B_{\beta,\alpha}$, $0

As a hazardous waste, pickling waste liquor must be properly treated. An alternative consists in promoting the formation of ferrous salts from this residue, due to its higher ferrous content. Since FeCl2·4H2O is widely used in several applications, obtaining pure crystals of this material appears to be an interesting prospect. However, this compound has scarcely been investigated. In the present work, FeCl2·4H2O crystals have been obtained from pickling waste liquors. Their structural and morphological characteristics have been investigated by X-ray diffraction, scanning electron microscopy as well as Mössbauer spectroscopy. In addition, the photoluminescence study of the obtained samples was also assessed. It was observed that after some aging time, the obtained crystals change in colour from green to more yellowish. So, the aged sample has also been evaluated, and their structural characteristics are compared with the original crystals. Despite this, the obtained crystals exhibit a FeCl2·4H2O structure, which is not modified with the aging of the sample.

During the creation and integration of a health care system based on medical knowledge graphs, it is necessary to review and select the vocabularies and definitions that best fit the information requirements of the system being developed. This implies the reuse of medical knowledge graphs; however, full importation of knowledge graphs is not a tractable solution in terms of memory requirements. In this paper we present a modularization-based method for knowledge graph reuse. A case study of graph reuse is presented by transforming the original model into a lighter one.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible to occur and hence lead to economic and human catastrophes. The aim of this document is precisely to characterise the mechanical crack growth behaviour of the 51CrV4 spring steel representative of leaf springs under cyclic conditions, that is, crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio are also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

: Polymer single screw extrusion is a major industrial processing technique used to obtain plastics products. To assure high outputs, tight dimensional tolerances, and excellent product performance, extruder screws may show different design characteristics. Barrier screws, which contain a second flight in the compression zone, have become quite popular as they promote and stabilize polymer melting. Therefore, it is important to design efficiently extruder screws and decide whether a conventional screw will do the job efficiently, or a barrier-screw should be considered instead. This work uses multi-objective evolutionary algorithms to design conventional and barrier screws (Maillefer screws will be studied) with optimized geometry. Processing of two polymers, Low Density Polyethylene and Polypropylene, is analyzed. A methodology based on the use of Artificial Intelligence (AI) techniques, namely data mining, decision making and evolutionary algorithms, is presented and utilized to obtain results with practical significance, based on relevant performance measures (objectives) used in the optimization. For the various case studies selected, Maillefer screws were generally advantageous for processing LDPE, while for PP the use of both types of screws would be feasible.

Hazelnut shells (HS), scientifically known as Corylus avellana L. shells, are a waste produced in companies that process nuts. The main objective of this study was to find an efficient way to maximize the chemical potential of HS by solubilizing the hemicelluloses, which could then be used to recover sugars and at the same time increase the lignin content of this material in order to produce adhesives or high strength foams. In order to optimize the pre-hydrolysis process, two different temperatures (160 and 170 C) and times varying from 15 to 180 min were tested. All the remaining solid materials were then liquefied by polyalcohols with acid catalysis. The chemical composition of hazelnut shells was determined before and after the pre-hydrolysis. All the process was monitored by FTIR-ATR by determining the spectra of solids and liquids after pre-hydrolisis and liquefactions steps. The highest solubilization of hazelnut shells was found for 170 C and 180 min, resulting in a 25.8% solubilization. Chemical analysis after the hydrolysis process showed a gradual increase in the solubilization of hemicelluloses as both the temperature and time of the reactor were increased. Simultaneously, the percentages of α-cellulose and lignin in the material also increased with rises in temperature and duration. FTIR-ATR allowed for the detection of significant spectral changes in the hazelnut shells from their initial state to the solid residue and further into the liquefied phase. This confirmed that pre-hydrolysis was effective in enhancing the chemical composition of the material, making it more suitable for the production of adhesives or polyurethane foams with enhanced mechanical strength.

The bean weevil (Acanthoscelides obtectus (Say.)) is one of the main pests of stored beans in the world. Heterogeneous Inbreed Families (HIF) Population of Near Isogenic Lines (NILs) could be an exceptional strategy to study the inheritance of the resistance against A. obtectus. We developed a HIF population of NILs of R-bufa-80-12 (Phaseolus vulgaris) to study the inheritance related to bean weevil resistance and to search NILs with high resistance to the pest within the HIF population. The objective of this research was to study the inheritance in a HIF population and to identify the best lines to provide weevil resistance in bean breeding for commercial genotypes that could reduce pesticide applications. To achieve this objective, we developed a set of 148 NILs which were near-homozygous in the genome, except in the region under study. The HIF were evaluated in two environments under natural infestation with A. obtectus in free choice bioassays in a warehouse highly infested. The population showed wide variability for the traits studied, from 17.2 to 29.2 g for 100 seed weight, 0.0-0.8 for consumption in grams, 2.0-30.0 for consumption in percent and 1.2-9.6 for preference (number of adults in the bottle to the end of the experiments. The heritabilities for resistance traits were from very low to low 0.0 to 0.19. The heritability for 100 seed weight was the highest, with a value of 0.90. All traits studied in this research have a normal distribution, so they are considered to be quantitatively inherited. However, a great variability was found for the traits studied, which allows selecting lines with a high level of resistance within the R-bufa-80-12 HIF population. All traits studied in present research are of quantitative inheritance. The best lines of the HIF population for resistance to A. obtectus were the Line-45, Line-129, Line-124, Line-108 and Line-47.

Human infection caused by the SARS-CoV-2 virus, called COVID-19, is a new pandemic with devastating effects worldwide. Science seeks the rational and systematic explanation of phenomena. In pandemics, decisions on prevention and treatment of people should be consistently taken, supported by scientific knowledge and ethical principles to produce more good than harm. At first, prospective observational studies to systematically collect patient data, correlating protective or therapeutic interventions with outcomes to assess effectiveness and safety, should be prioritized as the most appropriate type of study. The proposed protocol in this article aims to provide doctors with information on the reduction of harm in early COVID-19 patients by applying individualized interventionist or expectant therapeutic strategies, respecting the autonomy and preferences of physicians and patients in clinical decision-making. The evaluation of the clinical status, besides laboratory confirmation of COVID-19, comprises an individualized symptom score for each patient, a global self-perception scale of the severity of the disease, a clinical progression scale developed by the WHO for clinical studies in COVID-19 and, at the first consultation, doctors´ overall impression on the clinical prognosis. The analysis of anonymized data should preferably use descriptive and inferential statistical resources. The case report form is available for free use in the protocol, along with examples of patient informed consent forms for the prescription of off-label medications and authorization to use the data. Their results may be useful to indicate interventions that are candidates for efficacy trials, in randomized controlled trials, with a higher chance of success. It respects the autonomy and preferences of doctors and patients to decide the best options for treatment in uncertain situations. It also allows the gathering of useful information for future more rigorous clinical trials, trying to link science, ethics, and personal clinical experience.

The number of physical devices connected to the Internet such as vehicles, household appliances and other "things" has been steadily increasing in recent years, thus forming the basis for the Internet of Things (IoT). IoT ecosystem extends beyond country borders and application domains, combining thousands of versatile devices that differ in terms of their structures, capabilities, and available resources. It is therefore not surprising that the landscape of wireless communication technologies and the degree of IoT devices available today is excessively broad and diverse. Interference between networks leads to frame collisions and consequent packet loss. Frame collisions occur when two or more packets overlap in time and frequency and use the same Long Range (LoRa) parameters, i.e. the same Spreading Factor (SF), Bandwidth (BW) and Carrier Frequency (CF). When most devices use the same configuration, collision probability is higher. The probability of frame collisions is also affected by traffic characteristics, particularly the periodicity of the transmission and the payload size. Larger payload sizes and more frequent transmissions accumulate with higher Time on Air (ToA) and channel occupancy [1]. Transmission powers and the location of the gateways also influences this situation. The aim of this experimental work is to verify the effects of collisions and interference in Long Range Wide Area Network (LoRaWAN), regarding the periodicity of transmissions and the payload sizes in a context of an inter-SF interference scenario. And to validate measuring tools like Received Signal Strength Indicator (RSSI), ToA and Packet Delivery Ratio (PDR) in the reliability of a network. We validate our conclusions by analyzing ToA according with RSSI and different data sizes, the RSSI for different SFs and different data sizes and finally the packet loss through the PDR for a better understanding of the reliability of packet transmission in our link. In the end we conclude that in an environment with inter-SF interference, the choice of SFs and packet lengths impacts ToA. When dealing with multiple devices near gateways, different SFs and varying packet lengths can lead to increased latency and longer ToA. Consequently, the risk of packet loss becomes more significant, especially if the signal-to-interference ratio (SIR) is low. This limitation will therefore affect scalability, particularly in Non-Line-Of-Sight (NLOS) scenarios.

Research has shown that hands-on projects promote stem education, namely, via problem-solving. CanSat, literally 'satellite in a can', is a stem educational project promoted by the European Space Agency. This paper addresses this issue by researching this STEM project, which demonstrates how problem-solving can be achieved in secondary-level students within the framework of the CanSat. We use qualitative techniques of data collection and analysis. The results showed that students use sophisticated thinking strategies to process information within this interdisciplinary project: (a) cognitive testing, cognitive organization, cognitive regulation, and monitoring, in addition to computer language and physical–mathematical calculations, are cognitive and metacognitive behavior strategies revealed in the CanSat; (b) problem-solving was suggested as a specific model, where students’ higher cognitive and metacognitive ordering processes deepen in project development; (c) computational, lateral, or divergent and convergent thinking were detected as thinking types of students associated with and mobilized in the course of problem-solving, The findings of this research have practical implications for STEM education in space science. Hands-on projects using problem-solving are an essential strategy to promote STEM education. Additionally, they are a starting point to promote meaningful learning and new thinking types.

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

This paper analyses the evolution of the internal damage in two types of steel that show different fracture behaviours, with one of them being the initial material used for manufacturing prestressing steel wires, which shows a flat fracture surface perpendicular to the loading direction, and the other one being a standard steel used in reinforced concrete structures, which shows the typical cup-cone surface. 3mm-diameter cylindrical specimens are tested with a tensile test carried out in several loading stages and, after each of them, unloaded and analysed with X-ray tomography, which allows detection of internal damage throughout the tensile test. In the steel used for reinforcement, damage is developed progressively in the whole specimen, as predicted by Gurson-type models, while in the steel used for manufacturing prestressing steel-wire damage is developed only in the very last part of the test. In addition to the experimental study, a numerical analysis is carried out by means of the finite element method by using a Gurson model to reproduce the material behaviour.

Nutrient estimation in forest ecosystems through satellite images allows us to obtain accurate data, starting with data transformation from forest stands and the existing relationship with the spectral information of the image through modeling. The objective of the study was to quantify and validate the content of C, N, H in aboveground tree biomass in managed stands using spatial modeling and satellite images. This study was conducted during 2017-2018 in managed forest stands in San Juan Lachao, Oaxaca, Mexico. Fifteen 400 m2 experimental sites were selectively established, using a completely randomized experimental design of five silvicultural treatments with three replications. As part of data preprocessing, normality and homogeneity of variances assumptions were checked using the Shapiro-Wilk and Bartlett tests, respectively. From the pixels, data of the average of Normalized Difference Vegetation Index (NDVI) that surrounded the sampling sites were contrasted against the data obtained from forest inventory and the regression models to estimate C, N, H and biomass were generated. Models were validated by NDVI. With the models we estimated 0.95 t ha-1 biomass, which contains between 0.61 and 0.63 of C, 0.44-0.46 of N and 0.24 of H. The models generated had coefficients of determination (R2) of 0.85 to 0.87, which are significant parameters (p ≤ 0.0001). These results confirm that the use of Sentinel satellite images in the estimation of these elements in forest ecosystems based on the relationship between data inventory and the NDVI is highly reliable.

The objective of this article is to determine as conclusively as possible if the implementation of a UBI (universal basic income) would lead to a significant reduction in the working age population labour supply. If this were true, implementation of a UBI would be unsustainable. To do this, we will compile empirical evidence from studies over the last few decades on the effects of implementation of a UBI on employment. We apply the PRISMA methodology to better judge their validity, which ensures maximum reliability of the results by avoiding biases and making the work reproducible. Given that the methodologies used in these studies are diverse, they are reviewed to contextualize the results taking into account the possible limitations detected in these methodologies. While many authors have been writing about this issue citing experiences or experiments, the added value of this article is that it performs a systematic review following a widely tested scientific methodology. Over 1,200 documents that discuss the UBI/employment relationship have been reviewed. We found a total of 50 empirical cases, of which 18 were selected, and 38 studies with contrasted empirical evidence on this relationship. The results speak for themselves: despite a detailed search, we have not found any evidence of a significant reduction in labour supply; instead we found evidence that labour supply increases globally among adults, men and women, young and old; and the existence of some insignificant and functional reductions to the system such as a decrease in workers from the following categories: children, the elderly, the sick, those with disabilities, women with young children to look after, or young people who continued studying. These reductions do not reduce overall supply because it is largely offset by increased supply from other members of the community.

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

The construction industry is responsible for 40 to 45% of primary energy consumption in Europe alone. Therefore, it is essential to find new materials with a lower environmental impact in order to attain sustainable housing. This study aims to determine and compare the environmental impact of two clay samples forming a basis for the manufacture of traditional brick, a standard material in building construction; traditional red clay brick and a brick based on clay mixed with a biological ingredient. The samples of fired clay were manufactured at the laboratory scale, the results being valid exclusively as indicators for the extrapolation of the analysis to other studies. The results of the environmental impact of these formulations have been examined through an evaluation of life-cycle analysis (LCA), observing that the incorporation of biological pore forming agents led to a decrease of around 15 to 20% of all impact categories studied. Thus, the suitability of using biological-based additives in clay bricks was confirmed both for their constructive characteristics (lighter material) and increased energy efficiency (better thermal insulation) considering the environmental point of view.

This article presents a unique set of voltage and current data from a public building and acquired using a hybrid measurement solution that combines Python and Grafana. The transversal purpose consists of contributing to the community with a vision of the quality of the supply more oriented to the monitoring of the state of the network, providing a more realistic vision, which allows a better understanding, and the adoption of the best decisions to achieve the efficient energy management and thus optimize the operation and maintenance of power systems. The work focuses on higher order statistical estimators that, combined with exploratory data analysis techniques, improve the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination in the line of low-cost measurement solutions. It also incorporates the underlying benefit of the contribution to industrial benchmarking. The paper also includes a computational comparison between Python and LabVIEW to elicit the performance of the measurement solution.

Carbon nanotubes (CNTs) can be considered as semi-rigid all-carbon polymers. However, unlike conventional polymers that can form 3D networks such as hydrogels or elastomers through crosslinking with each other in solution, the cylindrical carbon lattice of CNTs was not believed to be directly crosslinkable in solution until our recent discovery of UV-defluorination driven direct CNT crosslinking. In this study, we further reveal that the UV-defluorination-driven crosslinked CNTs are metastable and can decompose more readily than fluorinated or pristine CNTs upon exposure to Raman laser irradiation. Specifically, we investigate the stability of UV-defluorinated single-walled and multi-walled fluoro-nanotubes using Raman spectroscopy under controlled varying laser power. The results indicate that both the defluorinated single-walled and multi-walled CNTs are thermally less stable than pristine CNTs or untreated fluorinated CNTs, which can be attributed to the strains on the crosslinking bonds created from the curved carbon lattice of linked CNTs. This instability, particularly evident under high-power laser irradiation, leads to combustion processes ignited at relatively lower temperatures that cause an extended burned area centered on the laser spot, offering potential future applications as mechanically robust, lightweight materials with feasible post-use degradation options.

Rare Earth Elements (REE), also known as Lanthanides (Ln3+), are a group of 17 elements showing peculiar physical and chemical properties. Unlike technological applications, very little is known about the physiological role and toxicity of Ln3+ on biological systems, in particular on microorganisms (e.g., bacteria), which represent the most abundant domains on our planet. Up to now, very limited studies have been conducted due to Ln3+ precipitation with some anions commonly present in the culture media. Therefore, the development of a minimal medium is essential to allow the study of Ln3+-microbial interactions, limiting considerably the precipitation as insoluble salts. In this regard, a new minimal culture medium capable of solubilizing large amounts of Ln3+, and allowing the growth of different microbial taxa, was successfully developed. Assays have shown that the medium is capable of solubilizing Ln3+ up to 100 times more than other common culture media and allowed the growth of 63 bacteria and 5 fungi. The kinetic growth of one yeast and one gram-positive bacterium has been defined, proving to support superior growth and biomass compared to other commonly used minimal media. Moreover, the sensitivity and uptake/absorption of a Bacillus stratosphericus strain was tested, highlighting its capability to tolerate concentrations up to 10 mM of either Cerium, Gadolinium or Lanthanum and accumulate different quantities of the three.

ABSTRACT: Psychological vulnerability (PV) and low mental health literacy correlate negatively with higher education students' positive mental health and health behaviours. Levels of mental health literacy limit self-help, adaptative coping strategies and academic success. However, few studies examine the significant differences between students' PV, mental health literacy, positive mental health (PMH) and modifiable behaviours variables. Identifying modifiable vulnerability factors is essential when seeking and providing professional help. Method: A cross-sectional descriptive study was conducted to investigate the differences between modifiable behaviours and PV, mental health literacy, and PMH in higher education students. A sample of 3,600 undergraduate students was recruited, mostly female (78.8%), with an average age of 23 years (SD = 6.68). Results: The majority were women, did not exercise, were dissatisfied with sleep quality time per night (62.1% sleep less than 7 hours per night) and did not engage in leisure activities. Also, most respondents had PV and low literacy levels, particularly at F1, and 67.9% scored in the flourishing group. Results showed significant differences (p<0.001) between gender, age, sleep, exercise, diet, leisure activities and PV, and PMH and literacy. Conclusions: The results identified modifiable vulnerability factors that underpin the design of intervention-targeted programmes to promote literacy and PMH in higher education campuses in Portugal to foster students’ well-being and self-help strategies.

While significant efforts have been made to recycle metals like lithium or cobalt for sustainable development in the battery industry, other high-value materials in the renewable energy sector, such as fluorinated carbon nanotubes (FCNTs), have not been adequately explored for re-utilization after their quality has been downgraded. FCNTs are expensive and energy-intensive to produce, making their sustainable use crucial. This study explores the potential of reusing quality-downgraded fluorinated carbon nanotubes (QD-FCNTs) as eco-friendly nano-additives in microgel composites for water retention applications. By employing a surface treatment process that avoids additional energy costs and environmentally harmful chemicals, we successfully enhanced the interaction between QD-FCNTs and microgels. This treatment significantly improved water retention time by reducing rapid evaporation, enabling sustained water release. Our findings demonstrate a promising avenue for the sustainable application of quality-downgraded fluorinated carbon nanotubes in agricultural and environmental technologies.

Life Cycle Assessment (LCA) methodology is increasingly prevalent in the quantification of environmental status in the building sector, following new legislative frameworks. Countries need to quantify and assess their environmental impacts as a previous base for regulation and decision making. In this context, standardised national data sets are being developed, based on consensus with manufacturers: sectoral Environmental Product Declarations. This study focuses on assessing these EPDs with the aim of providing relevant information for global decision-making, focusing on consistency and pointing out shortcomings. An assessment has been carried out both at national level, considering all sectoral EPDs and declared products, and at international level, with three common building materials (brick, steel and concrete). The results highlight the lack of traceability in the development and assessment of uncertainty, resulting in substantial discrepancies in reported impacts, especially in the later stages of the life cycle (up to 90% difference). Meanwhile, impacts such as Global Warming Potential or total renewable and non-renewable primary energy use show homogeneous values in the cradle-to-gate stages with differences generally less than 10%. The analysis of sectoral EPDs should be a design guide with environmental sustainability criteria, as the last section of this study attempts to focus on.

This systematic review investigates the failure rate and marginal bone loss (MBL) of dental implants placed in Solid-organ transplant (SOT) patients compared to healthy controls. Three databases (PubMed, Web of Sciences and the Cochrane Library) were searched up to June 2020 (PROSPERO CRD42019124896). Case-control and cohort studies reporting data failure rate and marginal bone loss (MBL) of dental implants placed in SOT patients were included. The risk of bias of observational studies was assessed through the Newcastle-Ottawa Scale (NOS). Four case-control studies fulfilled the inclusion criteria, all of low risk of bias. Meta-analyses revealed consistently lower implant failure rate than control populations at patient and implant levels. SOT patients had a significant difference of -18% (p-value <0.001) of MLB towards healthy patients. SOT status poses no serious threat to implant survival. Overall, this group of patients presented lower levels of dental implant failure rate and marginal bone loss compared to otherwise healthy patients. Further intervention trials with wider sample size and longer follow-ups are necessary to confirm these summary results.

Rising antimicrobial resistance (AMR) in Salmonella serotypes host-adapted to cattle is of increasing concern to the beef and dairy industry. The bulk of the existing literature focuses on AMR post-slaughter. In comparison, the understanding of AMR in Salmonella among pre-harvest cattle is still limited, particularly in Texas, which ranks top five in beef and dairy exports in the United States; inherently, the health of Texas cattle has nationwide implications for the health of the United States beef and dairy industry. In this study, long-read whole genome sequencing and bioinformatic methods were utilized to analyze antimicrobial resistance genes (ARGs) in 98 isolates from beef and dairy cattle in the Texas Panhandle. Fisher exact tests and elastic net models accounting for population structure were used to infer associations between ARGs and antimicrobial phenotypic profiles and metadata. Gene mapping was also performed to assess the role of mobile genetic elements in harboring ARGs. ARG were found to be statistically different between the type of cattle operation and Salmonella serotypes. Beef operations were statistically significantly associated with more resistance genes compared to dairy operations. Salmonella Heidelberg, followed by Salmonella Dublin isolates, were associated with the most ARGs. Additionally, specific classes of ARGs were only present within mobile genetic elements.

A novel hybrid CSP-PV power plant is presented. Instead of the integration used in current hybrid power plants, where part of the PV production is charged into the thermal energy storage system through electrical resistors, the proposed system integrates both PV and thermal solar fields using a high-temperature heat pump. Both the heat pump and the heat engine are based on Brayton supercritical CO2 thermodynamic cycles. Such integration allows for charging the molten salts storage as if a central tower receiver field supplied the thermal energy, whereas parabolic trough collectors are employed. Unlike conventional hybrid plants, where the storage of PV production leads to a decrease in power injected into the grid throughout the day, the power injected by the proposed system remains constant. The heat engine efficiency is 44.4%, and the COP is 2.32. The LCOE for a 50 MWe plant with up to 12 hours of storage capacity is 171 $/MWh, which is lower than that of existing CSP power plants with comparable performance. Although the cost is higher compared to a PV plant with batteries, this hybrid system offers two significant advantages: it eliminates the consumption of critical raw materials in batteries, and all the electricity produced comes from a synchronous machine.

Different polyurethanes (PUs) were synthesized with polycarbonate polyols of molecular weights 500, 1000 and 2000 Da. Their self-healing abilities at 20 °C were tested and their structural, thermal, and mechanical properties were analyzed. The PUs made with polycarbonates of molecular weights 500 (YC500) and 1000 Da (YC1000) exhibited self-healing at 20 °C and the self-healing time of YC1000 was the shortest. The high mobility of the short polymeric chains, the absence of crystallinity and the low degree of micro-phase separation favored self-healing at 20 °C in YC500. However, the presence of tack and the existence of allophanate species and urethane-carbonate and urea-carbonate hydrogen bonds disfavored self-healing. Consequently, the self-healing time at 20 °C of YC500 was longer than expected. On the other hand, YC1000 exhibited an “equilibrium” between the urethane-carbonate and urea-carbonate hydrogen bonds and carbonate-carbonate interactions among the soft segments, so a particular structural order was produced which was associated to its fastest self-healing at 20 °C. The PU made with the polycarbonate of molecular weight 2000 Da did not exhibit self-healing at 20 °C because its significant micro-phase separation and the presence of semi-crystalline soft domains.

Two polyurethanes (PUs) were similarly synthesized by reacting a cycloaliphatic isocyanate with 1,4 butanediol and two polyols of different nature (polyester, polycarbonate diol) with molecular weights of 1000 Da. The PU made with polycarbonate diol polyol (YCD) was the only showing intrinsic self-healing at 20 °C. For assessing the mechanism of intrinsic self-healing of YCD, a structural characterization by molecular weights determination, infrared and X-ray photoelectronic spectroscopies, differential scanning calorimetry, X-ray diffraction, thermal gravimetric analysis and dynamic mechanical thermal analysis was carried out. It was concluded that the self-healing at 20 °C of YCD was due to non-covalent dynamic exchange interactions among the carbonate groups of the soft segments. Therefore, the chemical nature of the polyol played a key role in developing PUs with intrinsic self-healing at 20 °C.

“Clickase” single-chain nanoparticles (Ck-SCNPs) are folded, enzyme-mimetic unimolecular polymeric nano-objects containing copper (Cu) ions able to catalyze the azide-alkyne Huisgen cycloaddition reaction in water and/or selected organic solvents, often in the presence of a reductant. Herein, we investigate the effect of morphology on catalytic activity of Ck-SCNPs synthesized by means of two different routes. An amphiphilic random copolymer composed of oligo(ethylene glycol) methyl ether methyl methacrylate (OEGMA) and 2-acetoacetoxy ethyl methacrylate (AEMA) units was used as precursor of these Ck-SCNPs. Folding was promoted through metal complexation between Cu(II) ions and beta-ketoester-containing AEMA moieties. The first route resulted in Ck-SCNPs1 containing Cu ions homogeneously distributed within each nanoparticle, whereas the second one promoted intra-chain clustering of Cu ions inside Ck-SCNPs2. A model fluorogenic “click” reaction between 9-(azidomethyl)anthracene and phenylacetylene, which was catalyzed either by Ck-SCNPs1 or Ck-SCNPs2, was used to unravel the effect of morphology on catalytic activity. This work paves the way to improve the catalytic activity of metallo-folded SCNPs through control of the intra-chain distribution of catalytic sites.

Making sustainable business models, especially in manufacturing, is a key approach for organizations to adopt in order to create more sustainable processes. New technologies are needed to implement new policies that can minimize the economic, environmental, and social consequences of industrial activity. Sustainable maintenance is decisive to guarantee the availability, reliability, and safety of assets, surpassing traditional maintenance policies and embracing the principles of the circular economy. The main objective of Maintenance 4.0 is to increase the lifespan and availability of the equipment by preventing unplanned downtime, reducing planned shutdowns, and improving safety. This research focuses on the integration of advanced Industry 4.0 tools with conventional monitoring and control techniques in process industries. The article suggests that while complex neural networks might provide good predictions, simpler solutions can generalize well and have lower prediction errors because they can capture the underlying relationships between variables in a specific asset better. The combination of maintenance function, Industry 4.0 tools, and advanced statistical solutions to obtain sustainable processes can facilitate organizational change and aid decision-making in equipment management. These solutions seek to reduce interruptions and expenses through the unnecessary utilization of labor and spare parts. All these considerations improve communication and data processing, resulting in improved maintenance of a hydrogen compressor in the petrochemical industry.