With a predominantly humid tropical climate and a large area for expanding agricultural activities, Angola has in principle favorable conditions for bioenergy production. The focus of this study was to evaluate the availability of suitable land for producing sugarcane. This crop is highly efficient in converting solar energy into biomass for energy purposes in Angola. To this end, the Global Agro-Ecological Zones database, GAEZ v4, developed by IIASA and FAO, with the aid of the QGIS version 3.22.5, has been used to identify areas suitable for sugarcane cultivation, considering four levels of suitability. Aiming at the sustainability of bioenergy production, areas dedicated to food production, protected areas, and areas with slopes above 16% were excluded. Under these criteria, this study identified the existence of 6.3 Mha in lands of good agricultural suitability, with water resources, corresponding to 5% of the Angolan territory, distributed in seven provinces of the country, especially in the provinces of Cuando Cubango and Cunene, where 85% of the very suitable land under irrigation is located. Adopting a model of agricultural productivity, assuming irrigation and adequate agricultural practices, such area could produce approximately 956 million ton of sugarcane annually, which is significantly higher than the current production in this country, This amount of feedstock, processed using current technology could potentially produce 81.3 GL of ethanol and 176,9 TWh of electricity with low GHG emission per year, able to mitigate, as a whole, circa 60.3 MtCO2-eq/year by displacing gasoline in light vehicles and diesel and natural gas consumed in power generation.

Background: Morphological alterations in intracranial pressure pulse waveform (ICPPW) secondary to intracranial hypertension (ICP >20 mmHg) and reduction in intracranial compliance (ICC) are well known indicators of neurological severity. To date, no studies have documented the ICPPW modifications after intracranial hypertension resolution with decompressive craniectomy (DC). The present study aimed to assess the morphological alterations in ICPPW among neurocritical care patients with and without DC, by comparing the variations of ICPPW features according to elevations in mean ICP values. Methods: Patients requiring ICP monitoring because of severe traumatic or spontaneous conditions were included. Mean ICP values were compared with ICPPW features (P2/P1 ratio, TTP and pulse amplitude). Elevation in ICP was produced by means of ultrasound-guided manual internal jugular veins compression. Results were distributed for three groups: intact skull (exclusive burr hole for ICP monitoring), craniotomy/large fractures (group 2) or DC (group 3). Results: 57 patients were analyzed. 21 (36%) presented no skull defects, whereas 15 (26%) had DC. ICP was not significantly different between groups: ±13.59 for intact and ±17.66 mmHg for DC, with ICP induced elevation also similar between groups (p= 0.56). Significant elevation was observed for P2/P1 ratio for groups 1 and 2, whereas reduction was observed in group 3 (elevation of ±0.09 for groups 1 and 2, whereas reduction of 0.03 for group 3, p=0.01). Conclusion: In the present study, intracranial pressure pulse waveform analysis indicated that intracranial compliance was significantly more impaired among decompressive craniectomy patients, although ICPPW indicated DC to be protective for further influences of ICP elevations over the brain. Analysis of ICPPW seems to be an alternative to real time ICC assessment.

We validated a new noninvasive tool (B4C) to assess intracranial pressure waveform (ICPW) morphology in a set of neurocritical patients, correlating the data with ICPW obtained from invasive catheter monitoring. Materials and Methods: Patients undergoing invasive intracranial pressure (ICP) monitoring were consecutively evaluated using the B4C sensor. Ultrasound-guided manual internal jugular vein (IJV) compression was performed to elevate ICP from the baseline. ICP values, amplitudes, and time intervals (P2/P1 ratio and time-to-peak [TTP]) between the ICP and B4C waveform peaks were analyzed. Results: Among 41 patients, the main causes for ICP monitoring included traumatic brain injury, subarachnoid hemorrhage, and stroke. Bland-Altman’s plot indicated agreement between the ICPW parameters obtained using both techniques. The strongest Pearson’s correlation for P2/P1 and TTP was observed among patients with no cranial damage (r = 0.72 and 0.85, respectively) in detriment of those who have undergone craniotomies or craniectomies. P2/P1 values of 1 were equivalent between the two techniques (area under the receiver operator curve [AUROC], 0.9) whereas B4C cut-off 1.2 was predictive of intracranial hypertension (AUROC 0.9, p < 000.1 for ICP > 20 mmHg). Conclusion: B4C provided biometric amplitude ratios correlated with ICPW variation morphology and is useful for noninvasive critical care monitoring.

The aim of this literature review was to present the novel imaging modalities elastography and contrast-enhanced ultrasonography. We provided an overview of the concepts and applications of each technique for the investigation of neoplastic and metastatic tumors in dogs and cats. Studies with elastography are based on the elasticity and deformation of the evaluated tissue. The information obtained from the different types of elastography can aid in the detection and differentiation of malignant and benign structures. Descriptions of elastographic studies in several organs and tissue in veterinary medicine reported that, in general, malignant tumors tend to be more rigid, and, therefore, less deformable than benign lesions or in comparison to the healthy parenchyma. Contrast-enhanced ultrasonography is based on the intravenous injection of contrast media constituted by microbubbles. This imaging modality can be performed in non-sedated animals and provides information on the tissue perfusion, allowing the investigation of macro- and micro-circulation. Studies with different organs and tissues were performed in dogs and cats and revealed a tendency of malignant tumors to present faster transit of the contrast media (time to wash-in, peak and wash-out). These advanced techniques can be associated with other imaging modalities, aiding important information to the well-established exams of B-mode and Doppler ultrasonography. They can be used as screening tests, potentially representing an alternative to the invasive sampling methods required for cytological and histopathological analysis.

Sugarcane plays a crucial role in global sugar and ethanol production. Conventionally, sugar-cane propagation involves planting billets. However, Brazilian researchers have introduced the innovative pre-sprouted seedlings (PSS) method, widely used in the MEIOSI (Simultaneously Occurring Interrotational Method) system. Although MPB has several advantages over the con-ventional method, its sensitivity to water scarcity is a challenge. The study aimed to evaluate the survival and growth of PSS inoculated with Bacillus licheniformis and Bacillus subtilis under differ-ent water regimes. The experiment was conducted in the field in a randomized block in strips (split-block) using a 2×4 factorial scheme consisting of two inoculation conditions (with and without bacteria) and four water regimes (0%, 33%, 66%, and 100% of the ideal irrigation). The bacteria increased the PSS's survival and water use efficiency in the field. In addition, inocula-tion increased root and shoot growth, as well as the nutrient uptake such as N, P, Mn, Zn, and Cu, which resulted in a higher number of stalks per meter and, therefore, a higher multiplica-tion rate in the MEIOSI system. Inoculation proved to be a promising alternative for establishing PSS under water restriction.

The urban mangrove of the Vitória Bay, Espírito Santo, Southern Brazil suffers from anthropogenic impacts, which interfere in the foliar spectral response of its species. Identifying the spectral behavior of these species and creating regression models to indirectly obtain structure data like the Leaf Area Index (LAI) are powerful environmental monitoring tools. In this study, LAI was obtained in 32 plots distributed in four stations. In situ LAI regression analysis with the SAVI resulted in significant positive relationships (r² = 0.58). Forest variability regarding the degree of maturity and structural heterogeneity and LAI influenced the adjustment of vegetation indices (VIs). The highest regression values were obtained for the homogeneous field data, represented by R. mangle plots, which also had higher LAI values. The same field data were correlated with SAVI of a RapidEye image for comparison purposes. The results showed that, images obtained by a UAV have higher spatial resolution than the Rapideye image, and therefore had a greater influence of the background. Another point is that the statistical analysis of the field data with the IVs obtained from the RapidEye image did not present high regression coefficient (r² = 0.7), suggesting that the use of VIs applied to the study of urban mangroves needs to be better evaluated, observing the factors that influence the leaf spectral response.

Spacetime torsion is known to be highly suppressed at the end of inflation, called preheating. Of course this fact does not avoid that metric could affect the cosmic dynamos at preheating phase as was showed by Bassett et al, in the general relativity (GR) case. In this paper, is to show that a torsionful magnetogenesis in QED effective lagrangean, drives either a torsion damping or an amplification mechanism or dynamo effect, depending upon torsion chirality. The present extension of Basset et al theory yields a new magnetic field expression $B\sim{a^{(1\pm{\beta})}}$, obtained from dynamo equation in QED. Here a cosmic factor ${\beta}=g_{T}{\eta}k$ is present. In a second example we find Higgs inlationary fields in Einstein-Cartan gravity thick domain walls (DWs). Recently a moodified Einstein-Cartan gravity was given by M Shaposhnikov et al [PRL (2020)] to obtain higgs like inflatons as a portal to dark energy.

The Nordic countries are practically always well positioned in the main international economic, social and sustainability indices and recommending the scientific literature that the variables that these indices intend to measure translate into sustainable economic growth, with this unprecedented empirical study we intend to verify through the ARDL methodology for space temporal 2004 -2018 if the maintenance of high scores in these indexes translates into effective economic growth. The ARDL methodology has the advantage of giving us short- and long-term coefficients. Using four of the main international indices, we conclude that for Nordic countries for economic growth, economic freedom is of no significance and business-friendly regulation is the most important variable. A fundamental discovery in our study (in which Granger's Causality complements the ARDL methodology) is that these countries have been able to adapt perfectly to the globalization process and that entrepreneurship has worked as an important contribution to the continued economic and social success of these countries, allowing them to continue to enjoy their “Nordic Welfare States” in these uncertain and troubled times. These variables have contributed to its economic and social sustainability.

The design of more efficient photosensitizers is a matter of great importance in the field of cancer treatment by means of photodynamic therapy. One of the main processes involved in the activation of apoptosis in cancer cells is the oxidative stress on DNA once a photosensitizer is excited by light. As a consequence, it is a matter of great relevance to investigate in detail the binding modes of the chromophore with DNA, and the nature of the electronically excited states that participate in the induction of DNA damage, for example, charge-transfer states. In this work, we investigate the electronic structure of the anthraquinone photosensitizer intercalated into a double-stranded poly(dG-dC) decamer model of DNA. First, the different geometric configurations are analyzed by means of classical molecular dynamics simulations. Then, the excited states for the most relevant poses of anthraquinone inside the binding pocket are computed by an electrostatic-embedding quantum mechanics/molecular mechanics approach, where anthraquinone and one of the nearby guanine residues are described quantum mechanically to take into account intermolecular charge-transfer states. The excited states are characterized as monomer, exciton, excimer and charge-transfer states based on the analysis of the transition density matrix, and each of these contributions to the total density of states and absorption spectrum is discussed in terms of the stacking interactions. These results are relevant as they represent the footing for future studies on the reactivity of anthraquinone derivatives with DNA and give insights on possible geometrical configurations that potentially favor the oxidative stress of DNA.

Recently Palle has investigated the chiral vorticity and Cartan torsion in neutrino asymmetries. In his case he addressed this problem in Goedel s like anisotropic Einstein-Catan cosmology. In this paper we discusse how these ideas applied to sheared Bianchi types I Einstein-Cartan (EC) neutrino amisotropic cosmology, affect the handness of neutrinos in the universe. Actually here a novel concept of the chiral metric is introduced where metric functions also possess two distinct signs as in neutrino flipping or helicity. The axial anomaly equation for neutrinos in the presence of torsion and metric chirality is shown to produce left-handed neutrinos from right-handed torsion. Metric chirality is shown to be able to define how the metric would behave far away of neutrino density. Chiral flipping of the chiral neutrinos in the presence of torsion is also investigated. It is shown that when the chiral torsion is left-handed the chemical chiral potential vanishes as the universe expands.

Recent advancements in Artificial Intelligence (AI), Deep Learning (DL), and computer vision have revolutionized various industrial processes through image classification and object detection. State-of-the-art Optical Character Recognition (OCR) and Object Detection (OD) technologies, such as YOLO and PaddleOCR, have emerged as powerful solutions for addressing challenges in recognizing textual and non-textual information on printed stickers. However, a well-established framework integrating these cutting-edge technologies for industrial applications still needs to be discovered. In this paper, we propose an innovative framework that combines advanced OCR and OD techniques to automate visual inspection processes in an industrial context. Our primary contribution is a comprehensive framework adept at detecting and recognizing textual and non-textual information on printed stickers within a company, harnessing the latest AI tools and technologies for sticker information recognition. Our experiments reveal an overall macro accuracy of 0.88 for the sticker OCR across three distinct patterns. Furthermore, the proposed system goes beyond traditional Printed Character Recognition (PCR) by extracting supplementary information, such as barcodes and QR codes present in the image, significantly streamlining industrial workflows and minimizing manual labor demands.

Malaria remains an important and challenging infectious disease, and novel antimalarials are required. Benzyl isothiocyanate (BITC), the main breakdown product of benzyl glucosinolate, is present in all parts of Tropaeolum majus L. (T. majus) and has antibacterial and antiparasitic activities. To our knowledge, there is no information on the effects of BITC against malaria. The present study evaluates the antimalarial activity of BITC and T. majus seeds, leaves, and stems aqueous extracts. We used flow cytometry to calculate the growth inhibition (GI) percentage of the extracts and BITC against unsynchronized cultures of chloroquine-susceptible Plasmodium falciparum (P. falciparum) 3D7-GFP strain. Extracts and/or compounds with at least 70% GI were validated by IC50 estimation against P. falciparum 3D7-GFP and Dd2 (chloroquine-resistant strain) unsynchronized cultures by flow cytometry, and the resistance index (RI) was determined. T. majus aqueous extracts showed some antimalarial activity higher in seeds than in leaves or stems. BITC’s GI was comparable to chloroquine’s. BITC’s IC50 was similar in both strains, thus a cross-resistance absence with aminoquinolines was found (RI < 1). BITC presented features that could open new avenues for malaria drug discovery.

The effects of the solvent used for the active layer materials of an OLED based on TADF emitters plays a fundamental role in solution-deposited devices. This work focuses the effects on the performance of different solvents employed to fabricate a very simple two organic layer OLED based on a green TADF emitter, under the concept of host:guest matrix. From the different results of the main figures of merit, it was possible to conclude that the OLED that used toluene as solvent for the active layer reached a maximum EQE of 14%, almost the maximum already obtained for this emitter in more complex device structures. With the analysis of the charge transport processes, it was possible to establish an explanatory model for the obtained results. Through impedance spectroscopy, additional characterization about the nature of charge transport processes was carried out. With these results, it was possible to corelate the relaxation times, with the electrical properties of the active layer, and infer about the interaction between the electrical charges and the defect levels opening new possibilities to further development in the printed OLEDs.

Coronaviruses are pathogens recognized for having an animal origin, commonly associated with terrestrial environments. However, although in a few cases, there are reports of their presence in aquatic organisms like fish, frogs, waterfowls and marine mammals. None of these cases has led to human health effects when contact with these infected organisms has taken place, whether they are alive or dead. Aquatic birds seem to be the main group carrying and circulating these types of viruses among healthy bird populations. Although the route of infection for CoVID-19 by water or aquatic organisms has not yet been observed in the wild, the relevance of its study is highlighted because there are cases of other viral infections known to have been transferred to humans by aquatic biota. It is encouraging to know that aquatic species, such as fish, marine mammals, and amphibians, shows very few cases of coronaviruses and that some other aquatic animals may also be a possible source of cure or treatment against then, as some evidence with algae and marine sponges suggest.

IgY antibodies are found in the blood and yolk of eggs. Several studies show the feasibility of utilising IgY for immunotherapy and immunodiagnosis. These antibodies have been studied because they fulfil the current needs for reducing, replacing, and improving the use of animals. Affinity and avidity represent the strength of the antigen-antibody interaction and directly influence antibody action. The aim of this review was to examine the factors that influence the affinity and avidity of IgY antibodies and the methodologies used to determine these variables. In birds, there are few studies on the maturation of antibody affinity and avidity and these studies suggest that the use of an adjuvant, type of antigen, strain of the animal, number of immunisations, and time interfere with the affinity and avidity of IgY antibodies. Regarding the methodologies, most studies use chaotropic agents to determine the avidity index. Studies involving solution phase and equilibrium titration reactions are also described. These results demonstrate the need for standardisation of methodologies for determination of affinity and avidity so that further studies can be performed to optimise the production of high avidity IgY antibodies.

The perceived poor performance of publicly traded companies on their sustainability commitments and the quality of sustainability reporting has prompted stakeholders to consider the economic, environmental, and social impacts of corporate activities. Economic activities have led to various threats in the form of climate change, pollution, greenhouse gas emissions, natural disasters, and other issues that have negatively impacted the environment and stakeholders. Companies are expected to report to stakeholders on their sustainability performance, but reality proves that present reporting falls below stakeholders’ expectations mainly due to its still voluntary nature. The present study aims to provide a literature review of the relationship between sustainability reporting and the role of companies governance, especially observing if climate change requirements and energy-needed changes are being accounted. Results highlight mixed evidence for the influence of board governance attributes, providing interesting insights for research advancement. The study has practical implications for businesses, regulators, governments, and other stakeholders in their policy deliberations and investment decisions. Further empirical studies are recommended to re-examine sustainability reporting using the variables identified as important factors and gaps in this study and other board characteristics to improve the generalizability of the results.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

The concrete sector is known for its significant contribution to the CO2 emissions. There are two main contributing factors for this situation: the large amount of concrete consumed per year on the planet and the high CO2 released from Portland cement manufacture, the key binding agent in concrete. To face the consequent sustainability issues, diverse strategies have been explored on the carbon capture and storage potential of cementitious materials. This paper addresses the potential of storing CO2 in concrete during the curing stage, applied to the precast Portuguese industry. To this purpose, it was assumed that CO2 will become a waste that will require an outlet in the future, considering that carbon capture will become mandatory in many industries. This work concluded that the net benefit in terms of carbon retention is positive for the process of storing carbon in concrete during the curing stage. More specifically, it was demonstrated that the additional emissions from the introduction of this new operation are only 10% of the stored amount, returning a storage potential of 76 000 tonnes of CO2 yearly. Moreover, the overall net reduction in the concrete life cycle averages 9.4% and 8.8% for precast elements and only non-structural elements, respectively. When a low cement dosage strategy is coupled with carbonation curing technology, the overall carbon net reduction is estimated to be 45%.

We aimed to assess whether play behavior can be used as a welfare indicator for farmed spotted pacas (Cuniculus paca) by examining its association with other positive welfare markers including affiliative behavior and low-amplitude vocalizations. We submitted six groups of spotted pacas (one male/two females per group) (N=18) to an ABA experimental design (A1/A2: without ball; B: with three boomer balls). Play behavior occurred only during phase B (mean=35.5s, SE=6.4). Spotted pacas spent more time in affiliative and exploratory behaviors, while they spent less time engaging in agonistic interactions during phase B than in both control phases (A1 and A2) (P<0.05). Moreover, spotted pacas emitted more low-amplitude bark vocalizations during phase B than during either control phase (P<0.05), which have previously been shown to indicate a positive affective state and low arousal level. Because the expression of play was associated with a decrease in aggression, an increase in affiliative behavior, and an increase in low-amplitude barking, indicating thus a positive state, we suggest that play behavior can be used as a non-invasive indicator of positive welfare in this species.

Software defect prediction models enable test managers to predict defect-prone modules and assist with delivering quality products. A test manager would be willing to identify the attributes that can influence defect prediction and should be able to trust the model outcomes. The objective of this research is to create software defect prediction models with a focus on interpretability. Additionally, it aims to investigate the impact of size, complexity, and other source code metrics on the prediction of software defects. This research will also assess the reliability of cross-project defect prediction. Well-known machine learning techniques such as support vector machines, k-nearest neighbors, random forest classifiers, and artificial neural networks were applied to publicly available PROMISE datasets. The interpretability of this approach has been demonstrated by SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) techniques. The developed interpretable software defect prediction models showed reliability on independent and cross-project data. Finally, the results demonstrate that static code metrics can contribute to the defect prediction models, and the inclusion of explainability assists in establishing trust in the developed models.

Living beings are composite thermodynamic systems in non-equilibrium conditions. Within this context, there are a number of thermodynamic potential differences (forces) between them and the surroundings, as well as internally. These forces lead to flows, which, ultimately, are essential to life itself. Living beings are under the pressures of natural selection, thus are biological flows as well. At the same time, the maintenance of homeostatic conditions, the tenet of physiology, demands regulation of these flows by control of variables. However, due to the very nature of these systems, regulation of flows and control of variables become entangled in closed loops. Therefore, the search for adaptation in flows takes a different path than the search for adaptation in morphological traits. Being at the roots of transfer processes, thermodynamic criteria turn out to be as natural physical candidates. Likewise, being at the roots of physiology, control turns out to be as a natural biological candidate in that path. Here we show how to combine entropy generation, with respect to a generalized process, and control of parameters (in such a generalized process) in order to create a criterium of optimal ways to regulate changes in generalized flows.

It's been a growing concern that many microbes are developing resistance against many antibiotics, lowering the effectiveness and progress expected from that treatment option. To overcome the re-sistance developed by microbes, metallic and non-metallic-based nanoparticle treatments are starting to present a very promising approach. Furthermore, polyurethanes are used in a wide range of biomedical applications due to their variety of physical-chemical, mechanical, and structural properties, and biotic and abiotic degradation. They are widely used in bio-imaging procedures when metallic-based filler particles are incorporated, making the final product radiopaque. It would be advantageous, however, if polyurethanes with intrinsic radiopacity could be produced in their synthesis, avoiding a series of disadvantages in the processing and final product and also presenting potential antimicrobial activities. This review’s objective was to study the radiopacifying charac-teristics of nanoparticles as well as the physical principles of radiopacity and the variety of medical applications of polyurethanes with nanoparticles. It was found in this study that the synthetization of radiopaque polyurethanes is not only possible but also that the efficiency of synthetization was improved when using atoms with high electron density as part of the back chainbone or grafted, making them great multipurpose materials.

Traditional population-based metaheuristic algorithms are effective in solving complex real-world problems but require careful strategy selection and parameter tuning. Parameter-less population-based optimization algorithms have gained importance due to their simplicity and efficiency. However, research on their applicability for solving large systems of nonlinear equations is still incipient. In this paper, a systematic review and detailed description of metaphor-less optimization algorithms is made, including the Jaya algorithm, the main Jaya variants for continuous optimization problems, with a focus on the Enhanced Jaya (EJAYA) algorithm, the three Rao algorithms, the best-worst-play (BWP) algorithm, and the very recent max-min-greedy-interaction (MaGI) algorithm. This paper also discusses a few previous parallelizations of the Jaya optimization algorithm, as well as recent GPU-based massively parallel implementations of the Jaya, Enhanced Jaya (EJAYA), Rao, and BWP algorithms developed by the authors. In addition, a novel GPU-accelerated version of the MaGI algorithm is proposed. The GPU-accelerated versions of the metaphor-less algorithms developed by the authors were implemented using the Julia programming language and tested primarily on GeForce RTX 3090 and NVIDIA A100 GPUs, as well as on Tesla V100S and Tesla T4 GPUs, using a set of difficult, large-scale nonlinear equation system problems. The computational experiments carried out produced quite significant speedups, which highlights the efficiency of the GPU-based versions of the metaphor-less algorithms developed for solving large-scale systems of nonlinear equations.

The overhead squat movement engages various bodily structures, and its interaction with three-dimensional elastic resistance along the kinetic chain approach remains insufficiently comprehended. This study aimed to describe the scapular kinematics during an overhead squat with the forearm in a supination exercise against an ER and clarify the therapeutic potential of this exercise on scapular rehabilitation. Using an electromagnetic tracking system, we recorded the three-dimensional shoulder kinematics of 19 male participants across seven humeral elevation positions. These positions were captured at 15-degree intervals, spanning from 30 to 120 degrees. The results indicated notable distinctions in scapular upward rotation [F(1,17)=6.09, p=0.024] and scapular posterior tilt [F(1,17)=6.04, p=0.025] between the phases. Furthermore, the interactions revealed significant differences in resistance and phases during humeral elevation for scapular upward/downward rotation [F(3.77,62.48)=7.99, p&lt;0.001], scapular internal/external rotation [F(2.98, 50.64, p&lt;0.001)], and scapular tilt [F(2.58, 43.81)=4.76, p=0.008]. The findings demonstrated that increasing resistance through elastic resistance played a pivotal role in enhancing scapular stability throughout the humerus elevation motion. This underscores the potential of the overhead squat movement as a valuable tool for both shoulder assessment and treatment.

Mobile applications, websites and social media networks are nowadays widely used communication tools. With the emergence of communication-related technologies in our lives and, consequently, the rise of social networks and mobile applications, health-related applications, generically encompassed under the term digital health, have become popular among the population. Smartphones and artificial intelligence have become very useful tools for health-related interventions. Because they are very accessible and cost-effective. They are also able to serve a larger number of communities than traditional interventions. Nutrition is not a field that has remained on the sidelines, and numerous mobile applications and technological tools have emerged that are intended to help and support diets or in the process of recovering from disease. However, many of these applications have limitations that are important to consider. For this reason, the aim of this review was to analyze the most widely used tools currently in use, discuss their advantages and disadvantages, and propose hypotheses for improvement.

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.

The permeation of dioxin-like pollutants, namely, chlorinated dibenzodioxins and dibenzofurans, through lipid membranes has been simulated using classic molecular dynamics (CMD) combined with the umbrella sampling approach. The most toxic forms of chlorinated dibenzodioxin and dibenzofuran, 2,3,7,8-tetrachloro-p-dibenzodioxin (TCDD) and 2,3,7,8-tetrachlorodibenzofuran (TCDF), and a dioleyl-phosphatidylcholine (DOPC) lipid membrane of 50 Å wide have been chosen for our study. The free energy profile shows the penetration process is largely favoured thermodynamically (DG≈-12 kcal/mol), with a progressively decrease of the free energy until reaching the energy minima at distances of 8Å and 9.5Å from the centre of the membrane for, respectively, TCDD and TCDF. At the centre of the membrane, both molecules display subtle local maxima with free energy differences of 0.5 and 1 kcal/mol with respect to the energy minima for TCDD and TCDF, respectively. Furthermore, the intermolecular interactions between the molecules and the lipid membrane have been characterized at the minima and the local maxima using hybrid quantum mechanics/molecular mechanics energy decomposition analysis (QM/MM-EDA). Total interaction energies of -17.5 and -16.5 kcal/mol have been found at the energy minima for TCDD and TCDF, respectively. In both cases, the dispersion forces govern the molecule-membrane interactions, no significant changes have been found at the local maxima, in agreement with the classical free energy profile. The small differences found in the results obtained for TCDD and TCDF point out the adsorption and diffusion processes through the cell membrane are not related to the different toxicity shown by these pollutants.

To examine the association of sleep quality and work from home with physical inactivity (PI) in leisure time during Covid-19 pandemic. A population-based household survey was conducted in two Bra-zilian municipalities from October to December 2020. Leisure-time physical activity (PA) was self-reported, and individuals who practiced less than 150 minutes of moderate PA or 75 minutes of vigorous PA weekly were classified as PI. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). WFH was assessed by: "Currently, how is your work routine regarding location? Associations were investigated using logistic regression and directed acyclic graphs (DAG) for the multivariate models. A total of 1,750 adults were interviewed, 69.1% were PI and 51.9% had poor sleep quality. Furthermore, 79.8% were not in WFH. In multivariate analysis, leisure PI was associated with poor sleep quality (OR:1.59: 95% CI: 1.02-2.48), and not being in WFH (OR:1.62: 95% CI: 1.05-2.50). When performing the combined analysis between these two factors, and who were not in WFH were four times more likely to be PI at leisure (OR=4.22;95%CI:2.05-8.65). The results indicate a high prevalence of PI, with poor quality sleep and non-WFH associated with leisure PI. These combined factors exacer-bated the occurrence of PI.

Cancer is a complex and heterogeneous disease, influenced by various factors that affect its progression and response to treatment. Although histopathological diagnosis is crucial for identifying and classifying cancer, it may not accurately predict the disease's development and evolution in all cases. To address this limitation, liquid biopsy has emerged as a valuable tool, enabling a more precise and non-invasive analysis of cancer. Liquid biopsy offers the ability to detect tumor DNA fragments, circulating tumor cells, and exosomes released by cancer cells into the bloodstream. Exosomes, in particular, have attracted significant attention in cancer research due to their specific protein composition, which can provide valuable insights into the disease. The protein profile of exosomes often differs from that of normal cells, reflecting the unique molecular characteristics of cancer. Analyzing these proteins can help identify cancer-associated markers that play critical roles in tumor progression, invasion, and metastasis. Ongoing research and clinical validation are essential to advance and effectively utilize protein biomarkers in cancer. Nevertheless, their potential to improve diagnosis and treatment is highly promising. This review discuss several exosome proteins of interest in breast cancer, particularly focusing on studies conducted in mammary tissue and cell lines in humans and experimental animals. Unfortunately, the studies conducted in the canine species are scarce. This emphasis sheds light on the limited research available in this field. Additionally, we present a curated selection of studies that have explored exosomal proteins as potential biomarkers, aiming to achieve the aforementioned benefits in breast cancer diagnosis, prognosis, monitoring, and treatment.

Canine mammary tumors (CMTs) are among the most common disease in female dogs and share similarities with human breast cancer, which have placed these animals as a model of study in comparative oncology. Metabolic reprogramming is one of them and is known as a hallmark of carcinogenesis whereby cells undergo adjustments to supply the high bioenergetic and biosynthetic demands of rapidly proliferating cells. However, such alterations are also vulnerabilities that may serve as therapeutic strategies which have been tested mostly in human clinical trials, but poorly explored in CMTs. In this dedicated review, we compilated the metabolic changes described for CMTs emphasizing the metabolism of carbohydrates, amino acids, lipids, and mitochondrial function. We observed here key factors associated with the presence and aggressiveness of CMTs, such as the increase in glucose uptake followed by enhanced anaerobic glycolysis via upregulation of glycolytic enzymes, changes in glutamine catabolism due to overexpression of glutaminases, raise in fatty acid oxidation and distinct effects depending on the lipid saturation, in addition to mitochondrial DNA which is a hotspot for mutations. Therefore, more attention should be paid to this topic given that targeting metabolic fragilities could improve the outcome of CMTs.

Amidst the rapid urbanization of cities worldwide, there is a pressing need for practical tools to manage and preserve the invaluable architectural heritage contained within them. This research introduces a systematic methodology for digitalizing and interpreting architectural heritage through augmented Reality (AR). The primary goal is to enhance the documentation, preservation, and accessibility of cultural assets, addressing both educational and touristic needs. Focusing on the historic district of Pelourinho in Salvador, Bahia, Brazil, the study showcases how 3D digitalization combined with AR can provide users with an interactive experience with historical structures, bridging the temporal divide. By integrating the digital replicas of historic buildings into a real-time environment, users gain enriched insights into these structures’ history, architecture, and cultural significance. Though the preliminary results underscore the potential of this approach, comprehensive user testing remains an area for future exploration. This paper thus highlights the potential of AR in historical and cultural preservation, suggesting its broader implications for education, tourism, and heritage management.

Background: When homeostasis is disturbed it can occur a pathological event named inflammation. The main drugs used in the treatment consist of the non-steroidal and steroidal anti-inflammatory drugs. However, the side effects remain an obstacle during the treatments. In this work we aimed to evaluate three new regioisomers analogues of naphthyl-N-acylhydrazone derivatives. Methods: Acute models of inflammation in vivo (formalin-induced licking and carrageenan-induced inflammation) as well as in vitro were used to evaluate the effects of LASSBio-2039, LASSBio-2040, and LASSBio-2041. Results: All three substances (at 1, 10 or 30 µmol/kg) presented significant effect in the in vivo model reducing leukocyte migration, nitric oxide (NO) and interleukin-1β production. It was observed that only LASSBio-2039 significantly reduced cell migration in vitro. None of the LASSBios did affect inducible nitric oxide synthase activity nor presented NO scavenger effect. It was not observed any toxic effect neither in vivo nor in vitro. The new regioisomers analogues of naphthyl-N-acylhydrazone derivatives presented a significant anti-inflammatory activity suggesting LASSBio-2039 with a direct effect in leukocytes migratory capacity. Conclusions: Taken together the data indicate that these substances present promising effect for de development a prototype for new drugs.

We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

The availability of rail infrastructure resources is a major driver of rail operations performance. To evaluate the impact of infrastructure provision, network simulation models can be used to accurately represent train traffic behavior in a wide range of scenarios. However, performing this task can result in a problem of high combinatorial nature as the number of factors and their associated levels increase. This requires more sophisticated techniques such as experimental design formulations or optimization modeling in order to yield satisfactory results. Yet the research in network simulation models for rail systems has hitherto been limited to simple what-if analysis, made up from few factors that cannot represent the whole spectrum of interventions. This is especially critical in closed-loop rail systems where trains are subject to various interferences. Local improvements can be misleading as the queues are merely transferred within the network. Considering this, we propose a hybrid simulation-optimization model to aid the strategic decision of minimizing supplementary capital costs in a heavy-haul Brazilian railroad under construction. As soon as the railroad is completed, investments in both loading and unloading rail terminals will be necessary. First, we developed a representative and flexible model capable of dealing with complex relations between variable infrastructure provision and the resulting operational performance. Then, we simulated this system to prove that the current set of proposed infrastructure resources cannot meet the transportation demands. Afterwards, we demonstrate that local improvements can be delusive as the queues are shifted from loading to unloading operations, reciprocally. Then, we solve an optimization model to define the minimal supplementary investment in order to meet the commercial goals of mining companies. This is done by choosing the best trackage configuration, equipment quantity and capacity and fleet sizing in 3 different production scenarios. The best values of the objective function were found by improving both loading and unloading equipment and increasing the number of trains.

Abstract: To compare the use of variable mechanical ventilation with conventional mechanical ventilation in porcine model of ARDS. Methods: Animals were divided into two groups (n = 6), conventional ventilation and variable ventilation with bi-oscillatory PEEP. For induction of ARDS, intravenous oleic acid was used until a P/F ratio of 200 to 300 mmHg. The animals were ventilated with pressure control, FiO2 1.0, inspiration-expiration ratio = 1:2, tidal volume 6 ml/kg with the initial respiratory rate adjusted to maintain an end tidal CO2 tension of 35 to 45 mmHg. Variable ventilation was characterized by the oscillation of PEEP from 5 to 10 cmH2O every 4 respiratory cycles, in convencional ventilation group PEEP was set from 5 cmH2O. Ventilatory, hemodynamic parameters, oxidative stress, antioxidant enzymes, Interleukin 8 (IL8) and 17-a (IL17a) and histological analyzes were evaluated; Results: The use of BiPEEP demonstrated improvement in lung compliance and PaO2 in relation to control. The levels of oxidative stress and antioxidant enzymes showed no significant difference. There was no difference in IL17a between groups. In IL8 there was a significant increase in the lung base of control in relation to BiPEEP, and a reduction in the apex of BiPEEP in relation to control. The control group showed changes in lung morphology characterized by cellular infiltrates, a thickening of the alveolar septae and atelectasis, which were attenuated in BiPEEP group; (4) Conclusions: The use of variable ventilation with bi-oscillatory level of PEEP demonstrates a potential ventilatory strategy in an experimental model of ARDS.

Assessing dietary inadequacies can contribute to understanding the nutritional vulnerabilities of a country. This study aimed to investigate nutrient intakes and micronutrient inadequacies in the Brazilian adult population, with an interest in different age subgroups. Cross-sectional study with 1812 individuals aged 19 to 65 years from a population-based study with a representative sample of Brazilian adults. Dietary intake was assessed by two 24-hour food recalls, and the probabilities of inadequate intake were estimated using the Dietary Reference Intake targets. Adequate macronutrient intake was over 99% for proteins, 84.7% for carbohydrates, and 80.7% for total fats. There was a high probability of inadequacy (above 90%) for vitamins D and E, but vitamin D inadequacy was very similar between sexes. In contrast, vitamin E was more likely to be inadequately consumed among women. A high probability of inadequacy (above 85%) of calcium and magnesium was found in the population, regardless of age group. Except for iron, the probability of inadequacy of other minerals increased with age. The results showed a relevant proportion of nutrient inadequacies, with those most at risk being women and older individuals, helping with better targeting and monitoring of public health policies that address nutritional problems in the population.

The main objective of this research was to analyze the relationship between socioeconomic and demographic indicators and the level of transparency of municipalities in the state of Maranhão. The transparency index was constructed based on the LRF and LAI and consisted of 32 items. Subsequently , for To identify which factors explain the level of transparency, a multiple linear regression was carried out, comparing the explanatory variables for the level of transparency adopted in this study. The sample consisted of municipalities in the State of Maranhão, totaling 211 municipalities, as 7 did not have a website. The results of the multiple linear regression model indicate that the IDHM, the log of total GDP, the GDP per capita and the variable log of POP explain the NT of the municipalities surveyed to the point of explain the level of transparency of the municipalities of Maranhão, only the IFDM did not show a relationship with the NT among the variables analyzed.

Using Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) in their information version, this paper extends their theoretical framework to incorporate instantaneous Granger Causality (iGC)’s frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC’s repercussions associated with Granger Connectivity where interactions mediated without delay between time series can be easily detected.

Quantum revival phenomena, wherein the wave function of a quantum system periodically returns to its initial state after evolving in time, are investigated in this study. Focusing on electrons confined within a quantum box with an impurity, both weak and strong coupling regimes are explored, revealing intricate relationships between impurity parameters and temporal dynamics. The investigation considers the influence of impurity position, impurity strength, and external factors such as aluminum concentration, temperature, and hydrostatic pressure on classical periods and revival times. Through analytical derivations and graphical analyses, the study elucidates the sensitivity of quantum revivals to these parameters, providing valuable insights into the fundamental aspects of quantum mechanics. While no specific physical applications are discussed, the findings offer implications for quantum heat engines and other quantum-based technologies, emphasizing the importance of understanding quantum revivals in confined quantum systems.

Cacipacoré virus (CPCV) was discovered in 1977 deep in the Amazon rainforest, from the blood of a black-faced ant thrush (Formicarius analis). As a member of the family Flaviviridae, genus orthoflavivirus, CPCV's intricate ecological association with vectors and hosts raises profound questions. CPCV’s transmission cycle may involve birds, rodents, equids, bovines, marsupials, non-human primates and bats as potential vertebrate hosts, whereas Culex and Aedes spp mosquitoes, have been implicated as potential vectors of transmission. The virus' isolation across diverse biomes, including urban settings suggests its adaptability as well as presents challenges for its accurate diagnosis and thus its impact on veterinary and human health. With no specific treatment or vaccine, prevention hinges on traditional arbovirus control measures. Here we provide an overview of the ecology, transmission cycles, epidemiology, pathogenesis and prevention, aiming in improving our ability to better understand this neglected arbovirus.

Metastatic melanoma patients have a poor prognosis with poor responsiveness to chemotherapy. BRAF V600E mutations have been detected in ~40% of melanoma patients. Vemurafenib is an oral agent licensed for patients with BRAF V600E mutation-positive inoperable and metastatic melanoma, which already presents resistance that leads to patient relapse and the serious side effects. In our study, we synthesized 5 new vemurafenib analogs, RF-86A, RF-87A, RF-94A, RF-94B and RF-96B, with structural improve-ments, in order to increase the anti-proliferative and anti-metastatic effect on human melanoma. We showed that the analogs were efficient in inducing cell death and reducing the migration of A375 cells, by inhibition of MMP-2 and MMP-9 activity, indicating that this action may be longer lasting comparing to the action of Vemurafenib.

Integrated crop-livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no-tillage (NT) with ryegrass as cover crop (C) and silage (S) were investigated. The soil micromorphological properties of the soil were analyzed using X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8×103), volume (c. 26%), and number of pores (c. 32%) in a rod-like shape. On the other hand, the MT(S), NT(C), and NT(S) systems showed higher tortuosities (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivities (c. 8.3×103, c. 6.9×103, and c. 6.2×103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.

Having as objective to reach a circular economy, it is important to maximize the Physical Asset’s Life Cycle. The evaluation of Physical Assets Life Cycle may have several approaches which may provide different results. These differences may not be very significant, but must be taken into consideration, because they have consequences in the manager decision. This permits to have a wider time interval to decide when to withdrawal the Physical Asset or to renewal it, and or if this ought to continue functioning because the profits are higher than the expenses, what allows to diminish waste and increase sustainability. These are some aspects that are discussed in this paper, which presents several models to evaluate the Physical Assets Life Cycle, considering the market value, devaluations methods and a more generalized way of Fisher’s Equation, which can include the Risk tax, among others. The results are discussed supported in data for simulation, which are used for each Econometric Model aiming to evaluate the differences among them. In all Models they are considered not only the expenses, namely of Investment and Functioning, but also the Profits, which permit to evaluate the Physical Asset Life Cycle in a holistic way. The models are very versatile, allowing to evaluate quantitatively the changing in the maintenance policies, the energy prices variations, the risk evaluation, the variation of profits according to the real market, and so on. The results demonstrated the robustness of the approach described and that maximize the Physical Assets Life Cycle allowing to minimize the consumption of world resources and, by consequence, it contributes for a more sustainable world.

Autoimmune thyroid disease refers to a spectrum of various diseases, with two extremes of clinical presentation, hypo-thyroidism (Hashimoto's thyroiditis), and hyperthyroidism (Graves-Basedow disease). Both conditions are character-ized by presenting a cellular and humoral autoimmune reaction, with an increase in the synthesis and secretion of an-tibodies directed towards various thyroid antigens, together with a phenomenon of thyrocyte necrosis and apoptosis (in Hashimoto's thyroiditis) and a persistent thyrotropin-receptor stimulation (in Graves-Basedow disease). The diagnosis of both entities is based on the clinical, laboratory and imaging findings. In this review, the usefulness of thyroid antibodies in the diagnostic approach to autoimmune thyroid disease is de-scribed.

The objective of this paper is to present an electromagnetic sensor that generates pulse inductance [1], integrated on an Unmanned Aerial Vehicle (UAV) which complements the current technology in this area, adding equipment to the detection of landmines. The electromagnetic sensor developed, locates landmines deployed during armed conflicts, which daily kill innocent people, block economic and social development, hinder the displacement of people, causing serious social and economic problems for many years. Flights can be made over mined areas allowing the identification of the exact location of each land mine.

Evidence on adult mammalian neurogenesis and scarce studies with human brains led to the idea that adult human neurogenesis occurs in the subgranular zone (SGZ) of the dentate gyrus and in the subventricular zone (SVZ). However, findings published from 2018 rekindled controversies on adult human SGZ neurogenesis. We systematically reviewed studies published during the first decade of characterization of adult human neurogenesis (1994–2004) – when the two-neurogenic-niche concept in humans was consolidated – and compared with further studies. The synthesis of both periods is that adult human neurogenesis occurs in an intensity ranging from practically zero to a level comparable to adult mammalian neurogenesis in general, which is the prevailing conclusion. Nonetheless, Bernier and colleagues showed in 2000 intriguing indications of adult human neurogenesis in a broad area including the limbic system. Likewise, we later showed evidence that limbic and hypothalamic structures surrounding the circumventricular organs form a continuous zone expressing neurogenesis markers encompassing the SGZ and SVZ. The conclusion is that publications from 2018 on adult human neurogenesis did not bring novel findings on location of neurogenic niches. Rather, we expect that the search of neurogenesis beyond the canonical adult mammalian neurogenic niches will confirm our indications that adult human neurogenesis is orchestrated in a broad brain area. We predict that this approach may, for example, clarify that human hippocampal neurogenesis occurs mostly in the CA1-subiculum zone and that the previously identified human rostral migratory stream arising from the SVZ is indeed the column of the fornix expressing neurogenesis markers.

In this work, the influence of catalyst reuse and reaction time on the yield and quality of organic liquid products (OLP) obtained in a cracking pilot plant at 450 °C and 1.0 atm has been systematically investigated. The distillation of OLP produced 04 (four) distilled fractions. The quality of the biofuels was certified by physical-chemical analysis, as well as FT-IR and GC-MS analysis. The experimental results showed the feasibility of applying the spent sodium carbonate twice in catalytic cracking of vegetable oils. The physical-chemical properties (density, viscosity, acid value, saponification value, and flash point) of OLP decrease as the reaction time increases. The distillation of OLP yields 62.35% (wt.), producing green-like gasoline, kerosene, and diesel fractions rich in hydrocarbons. Therefore, biofuels-like fractions produced by distillation of OLP have a great potential for replacing partially petroleum derived fuels.

Many neurodegenerative diseases are directly related to the formation of toxic protein aggregates, such as Parkinson’s and Alzheimer’s diseases, which are associated with the aggregation of alpha-synuclein (α-syn) and beta-amyloid (Aβ ), respectively. In this context, protein fibrils are the hallmark of these neurodegenerative diseases. In this sense, planning or designing compounds that are capable of preventing or reducing the formation of protein aggregation in the brain can be of fundamental importance for the curative treatment of these diseases. This work presents an in silico and experimental study to investigate the inhibitory potential of the ligands Octovespin (bioinspired by the wasp venom Polybia Occidentalis) and Fraternine-10 (bioinspired by the wasp venom Parachartergus fraternus wasp) against the aggregation of fibrils of the peptides Aβ(17-42) and α-syn, respectively. Using molecular docking and molecular dynamics simulations with 100 ns, the disaggregation capacity of these ligands was studied. The results obtained indicate that Octovespin and Fraternine-10 interact with the Aβ and α-syn protein fibrils throughout the simulation time. The RMSD values and the interactions with amino acids responsible for fibril aggregation demonstrate that both Octovespin and Fraternine-10 have a significant disaggregation potential, which corroborates the observations in vitro and in vivo. Furthermore, experimental results of Fraternine-10 demonstrate an anti-aggregation effect, indicating that it can promote the disaggregation of fibrils and prevent them from aggregating again to form oligomers. These discoveries qualify these molecules as potential candidates to become medicines against Parkinson’s and Alzheimer’s diseases.

During embryo development, the endoplasmic reticulum (ER) acts as an important site for protein biosynthesis, however, in vitro culture (IVC) can negatively affect ER homeostasis. Thereby, the aim of our study was to evaluate the effects of supplementation of tauroursodeoxycholic acid (TUDCA), an ER stress inhibitor, in the IVC of bovine embryos. Two experiments were carried out: Exp. 1: evaluation of blastocyst rate, hatching kinetics and gene expression of hatched embryos after being treated with different concentrations of TUDCA (50, 200 or 1,000 μM) in the IVC; Exp. 2: evaluation of the re-expansion, hatching, and gene expression of hatched embryos previously treated with 200 µM of TUDCA at IVC and submitted to vitrification. There was no increase in the blastocyst and hatched blastocyst rates treated with TUDCA in the IVC. However, embryos submitted to vitrification after treatment with 200 µM of TUDCA, increased hatching rate post-warming, together with a down-regulation in the expression of ER stress-related genes and the accumulation of lipids. In conclusion, this work showed that the addition of TUDCA during in vitro culture can improve the cryotolerance of the bovine blastocyst through the putative modulation of ER and oxidative stress.

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

Background: The 2021 “Universal Definition of Heart Failure (HF)” Proposed the following left ventricle ejection (LVEF) phenotype classification: ≤40%; HF with intermediate LVEF: between 41-49% and HF with preserved LVEF: ≥50%. LVEF represents the percentage of left ventricular ejected volume in each cardiac cycle and Cut-points considered statistically normal are: ≥52% in men and ≥54% in women. The prevalence HFpEF is of 35-60% among the HF phenotypes, with a facing to increase rates in relation to HFrEF and is associated with mortality rates similar to those of HFrEF. The pathophysiology of HFpEF is based on vascular and metabolic dysfunction, therefore, there is less neurohumoral stimulation compared to HFrEF. Methodology: A systematic review was performed to report of information related to Sacubitril-valsartan and the treatment of HFrEF. Terms related to “treatment” and “brazil” were used in the databases PubMed (MEDLINE) and Scientific Electronic Library Online (SCIELO). Results: Clinical trials testing drugs that modulate the neurohumoral system in patients with HFpEF failed to demonstrate benefit in the combined endpoint of reduced mortality/hospitalization due to HF compared to placebo to date. Sacubitril-valsartan is a drug with a mechanism of action surrogate the pathophysiological concept of HFpEF, it is safe and decreased endpoints of natriuretic peptides and left atrial structure in a phase II clinical study. Conclusions: The PARAGON-HF trial demonstrated that sacubitril-valsartan reduced the primary endpoint of the study when assessed the pre-specified subgroup of LVEF≤57% and improved the secondary endpoints of performance status and renal function in the population.

Abstract The processing of anatase ores by sulfuric acid digestion is well known for its low titanium dissolution yields, which makes the process economically and technically unfeasible. Generally, to enhance the dissolution of titanium from anatase, thermal processes along with acid and/or alkaline leaching are necessary. Few existing works report yields of direct digestion of anatase with sulfuric acid <48%. This study investigated the sulfuric digestion of anatase and yields around 80% were obtained at relatively mild conditions such as temperature at 220°C, sulfuric acid/concentrate ratio of 1:2 and 3 hours of reaction. A comprehensive characterization of anatase ore was also presented.

The purpose of this article is to conduct a bibliometric review of literary production in terms of market interdependence. We investigate the effect of contagion on agricultural commodities and identify the commodities and methods used in the most cited publications over the decades. For this, we used the SCOPUS database, sorting with Rayyan, Excel, and finally, the Bibliometrix/R-project. The results showed that corn, wheat, soybeans, cotton, and sugar are the most studied commodities. There is no uniqueness concerning the methods used to identify interdependence and the contagion effect. Also, it is possible to perceive the growing scientific interest concerning the subject, with a diversity of authors and magazines. However, there is a direction of the and magazines most cited articles for analyzing agricultural commodities and energy, demonstrated a worldwide trend of studies relating natural resources, biofuels, clean energy, and efficiency. In addition, countries like China and the United States stand out in this scientific scenario as the countries that produce the most articles.

As digitalization expands across all sectors, the economic toll of software defects on the U.S. economy reaches up to $2.41 trillion annually. High-profile incidents like the Boeing 787-Max 8 crash have shown the devastating potential of these defects, highlighting the critical importance of software testing within quality assurance frameworks. However, due to its complexity and resource intensity, the exhaustive nature of comprehensive testing often surpasses budget constraints. This research utilizes a machine learning (ML) model to enhance software testing decisions by pinpointing areas most susceptible to defects and optimizing scarce resource allocation. Previous studies have shown promising results using cost-sensitive training to refine ML models, improving predictive accuracy by reducing false negatives through addressing class imbalances in defect prediction datasets. This approach facilitates more targeted and effective testing efforts. Nevertheless, the generalizability of these models across different projects (cross-project) and programming languages (cross-language) remained untested. This study validates the model's applicability across diverse development environments by integrating various datasets from distinct projects into a unified, using a more interpretable ML approach. The results demonstrate that ML can support software testing decisions, enabling teams to identify up to seven times more defective modules with the same testing effort as a benchmark.

The fourth industrial revolution (4IR) can offer significant benefits to the construction sector, improving productivity, efficiency, collaborative efforts, and product quality while promoting safety and sustainability. However, research on the application of 4IR technologies in construction is scarce in developing countries. It is crucial to understand the ability of construction companies to adopt new technologies and identify factors influencing the success of technology implementation. In this study, a questionnaire-based survey was conducted with construction professionals to evaluate the level of technological development of the construction market in an emerging economy, assess the potential for innovation implementation, and identify factors that might influence technological development. Although respondents recognized the importance of digital transformation, the results showed that most innovations are in the early stages of implementation in the construction sector, particularly technologies that are essential for the consolidation of the 4IR. Understanding the factors underlying this reality can support the development of strategies to foster innovation and harness the advantages of the 4IR in the construction industry in developing countries.

Land Surface Temperature (LST) is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA) radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This work analyses calibration strategies, considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis – Satellite Application Facility to calibrate its LST algorithms applied both for current and forthcoming sensors.

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

The purpose of this review is to provide an overview of brain arteriovenous malformations (AVMs) and focus on their management. The therapeutic options differ in each case depending on the location, size, and adjacent anatomical content of the AVM. The surgical resection by microsurgery is the preferred therapeutic option for a small and superficial AVM not related to an eloquent area (e.g., Spetzler-Martin grades I and II). On the other hand, when facing a very large AVM (e.g., Spetzler-Martin grades IV and V), the conservative and symptomatic treatment remains the most common management option due to the high risk-benefit ratio of any intervention. The management of AVMs with features between these two extremes (e.g., Spetzler-Martin grade III) remains less stablished. Stereotactic radiosurgery usually is the option for deep and small AVMs. Embolization has been usually considered before surgery for occlusion of deep arterial supplies of an AVM or to decrease its nidus size. Young patients and AVMs with compact nidus are features that weight in favor of a surgical approach. For the minority of cases that have the AVM diagnosed before bleeding the most common recommendation is to treat conservatively and particularly to avoid embolization. In summary, surgery is the gold-standard approach to cure an AVM and the choice for small AVMs located in non-eloquent area and with superficial venous drainage; large AVMs are mostly treated conservatively; the treatment of AVM with intermediate features is tailored, chosen with the guidance of classification systems, and encompasses radiosurgery and pre-operative embolization.

Carbohydrates such as fructooligosaccharides (FOS) are associated with improved gastrointestinal health and prevention of excess body fat. We evaluated the long-term effects of high amounts of FOS on metabolic parameters, non-alcoholic fatty liver disease (NAFLD) and short-chain fatty acids (SCFA). Sixty C57BL/6 mice received diets for four months: control (C), normolipid rich in fiber (F), normolipid supplemented with FOS (FOS), high fat (HL), high fat with high fiber (HLF) and high fat with FOS (HLFOS). We analyzed: animal weight; body composition; food intake; fasting blood glucose; serum and liver lipid profile; liver and intestinal histologies; malondialdehyde (MDA), hepatic retinol and α-tocopherol; SCFA in the feces. Supplementation with FOS in a high-fat diet promoted less body weight gain and reduced liver and retroperitoneal adipose tissue weights compared to HL and HF. FOS prevented NASH and decreased alanine aminotransferase and serum cholesterol levels in experimental animal models of obesity and metabolic syndrome (MS). There was found statistical differences in the dosages of the three main SCFAs in feces (acetic, isobutyric and isovaleric acids). Long-term supplementation with high doses of FOS was effective in reducing weight, adiposity, NAFLD and serum cholesterol in C57BL mice with obesity and MS induced by a high-fat diet.

Our aim was to determine the secondary antibody deficiency profiles of patients in a mesoregion of São Paulo state, Brazil, focusing on infectious diseases. Demographic characteristics, clinical and laboratory data were obtained from electronic files; infections were classified as organ-specific and graded as mild, moderate, life-threatening, and fatal. Non-Hodgkin lymphoma (NHL) accounted for 30% of patients, nephrotic syndrome (NS) 25%; chronic lymphocyte leukemia 20%, and multiple myeloma 15%. Patients with NS were younger than those in other groups, and hypo-γ-globulinemia was detected in 94.1%, IgG <400 mg/dL in 60.0%, IgA <40 mg/dL in 55.0%, and CD19 <20 cells/mm³ in 30.0%. One hundred and one infections were found; 82.1% were classified as mild or moderate, 7.9% as life-threatening, and 1.9% as fatal. Respiratory tract infections were more prevalent (41.5%), and pneumonia accounted for 19.8%. Lower levels of infections were found in patients with NS compared with NHL (P=0.0001). Most patients progressed to hypo-γ-globulinemia and secondary antibody deficiency after treatment with immunosuppressants, and mild and moderate infections were predominant. These therapies are increasing in patients with different diseases, therefore monitoring hypo-γ-globulinemia and infections may help to identify patients at high risk for severe complications, antibiotic prophylaxis or treatment, and immunoglobulin replacement

This work investigated the effect of temperature and acid or alkalis chemical activation by pyrolysis of Açaí seeds (Euterpe Oleraceae, Mart.) on the yield of bio-oil, hydrocarbon content of bio-oil, and chemical composition of aqueous phase. The experiments were carried out at 350, 400, and 450 °C and 1.0 atmosphere, KOH and HCl activation, in laboratory scale. The acidity of bio-oils and aqueous phases determined by AOCS methods, while the chemical composition of bio-oils and aqueous phase by GC-MS and FT-IR. The bio-char characterized by XRD. For the activation with KOH, the XRD analysis identified the presence of Kalicinite (KHCO3), the dominant crystalline phase in bio-char, while an amorphous phase was identified in bio-chars for the activation with HCl. The yield of bio-oil, for the pyrolysis of Açaí seeds activated with KOH, varied between 3.19 and 6.79 (wt.%), showing a smooth exponential increase with temperature. The acidity of bio-oil varied between 12.3 and 257.6 mgKOH/g, decreasing exponentially with temperature, while the acidity of aqueous phase lies between 17.9 and 118.9 mgKOH/g, showing and exponential decay behavior with temperature, demonstrating that higher temperatures favor not only the yield of bio-oil but also bio-oils with lower acidity. For the pyrolysis experiments activated with HCl, the yield of bio-oil varied between 2.13 and 3.37 (wt.%), decreasing linearly with temperature, while that of gas phase varied between 17.91 and 37.94 (wt.%), increasing linearly with temperature. The acidity of bio-oil varied between 127.1 and 218.5 mgKOH/g, increasing with temperature, showing that higher temperatures did not favor the yield of bio-oil and bio-oils acidity. For the chemical activation with KOH, the FT-IR analysis of bio-oils identified the presence of chemical groups characteristics of hydrocarbons and oxygenates, while that of aqueous phase only groups characteristics of oxygenates. For the chemical activation with HCl, the FT-IR analysis of bio-oil and aqueous phases identified only the presence of groups characteristics of oxygenates. For the experiments with KOH activation, the GC-MS of bio-oil identified the presence of hydrocarbons (alkanes, alkenes, cycloalkanes, cycloalkenes, and aromatics) and oxygenates (carboxylic acids, phenols, ketones, and esters). The concentration of hydrocarbons varied between 10.19 to 25.71 (area.%), increasing with temperature, while that of oxygenates from 52.69 to 72.15 (area.%), decreasing with temperature. For the experiments with HCl activation, the GC-MS of bio-oil identified only the presence of oxygenates. Finally, it can be concluded that chemical activation of Açaí seeds with KOH favors the not only the yield of bio-oil but also the content of hydrocarbons while activation with HCl produced bio-oils with only oxygen compounds.

This work presents a new algorithm to resolve the problem of distribution network reconfiguration using the Tabu Search metaheuristic and voltage drop. The proposed method presents a different way to obtain the initial solution using the voltage drop, as well as a new way to generate a neighborhood of candidate solutions, based on randomness and the voltage drop, to perform a smooth and steady descent execution of the algorithm. The proposed algorithm has the main objective to reduce the active power losses in distribution networks, but it also achieves an refinement in the voltage profile. The proposed method was tested in two distribution systems, the 33-Bus and 94-Bus systems, commonly found and tested in the literature. The results of the tests show that the proposed method presents a low computational cost, achieves good solutions, and is better than the other methods found in the literature.

We consider open non-twist Hamiltonian systems represented by an area-preserving two-dimensional map describing incompressible planar flows in the reference frame of a propagating wave, and possessing exits through which map orbits can escape. The corresponding escape basins have a fractal nature that can be revealed by the so-called basin entropy, a novel concept developed to quantify final-state uncertainty in dynamical systems. Since the map considered violates locally the twist condition, there is a shearless barrier that prevents global chaotic transport. In this paper we show that it is possible to determine the shearless barrier breakup by considering the variation of the escape basin entropy with a tunable parameter.

Fluxgate magnetometers require calibration methods appropriate to their application levels and particularities; however the development of fully controlled calibration procedures presents a particular challenge regarding the inevitable influence of the local geomagnetic field and other external interferences when a laboratory with magnetically shielded walls is not available. In that context, we discussed the development of an automated calibration method for fluxgate magnetometers, considering those limitations in time and space, and avoiding some of the problems commonly found in other proposed solutions for the same challenge. For this task, we designed and built a new set of high level procedures, electronic systems and software, which perform active testing and automated calibration of fluxgate magnetometers, considering some resource constraints and employing instruments commonly found in electronic calibration laboratories.

The objective of this study was to assess the impact of different inoculation technologies on the aerobic biological semi-decomposition process of bokashi-type biofertilizer formulations. We examined their effects on the chemical and biological quality of the product, as well as their influence on the agronomic and nutritional characteristics of red-beet and cabbage crops in the field. The highest yields of field-grown beet crops were obtained from seedlings produced using the following treatments: bokashi biofertilizer + biodynamic preparations 502-507 BPB (62.6 Mg ha-1), bokashi + Chamomilla 12CH (60.2 Mg ha-1), and bokashi + Carbo vegetabilis 12 CH (56.3 Mg ha-1). These results corresponded to an increase of 60.9%, 54.7%, and 44.7%, respectively, compared to the yield of the control treatment (38.9 Mg ha-1). The increase in productivity of cabbage plants was higher in the treatment bokashi + Calcarea carbônica 12 CH (35.8 Mg ha-1), being 148.6% higher than the control (14.4 Mg ha-1).The content of moisture, carbon, nitrogen, C/N ratio, and pH H2O in the majority of the evaluated formulations, comply with the standards outlined in IN Nº 61, 2020, by Ministry of Agriculture, Fisheries and Supply, qualifying them as class "A" solid organic compound fertilizers.

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.

At the beginning of December 2019, a new type of coronavirus emerged, SARS-CoV-2. This virus causes COVID-19, a highly contagious disease that can initially present asymptomatically and can also lead to death. Our ecological study goal was to evaluate the incidence, mortality, and lethality rates for COVID-19 between the states of Espírito Santo and Minas Gerais, with time series analysis using secondary and public databases on COVID-19 from January 2020 to July 2022. Prais-Winsten linear regression was used for trend analyses. In 2020, the rate in Espírito Santo was 2.19 times greater than Minas Gerais. This trend continued in 2021, with Espírito Santo's rate being 1.29 times greater. In 2022, Espírito Santo's rate remained 2.65 times higher than Minas Gerais. Furthermore, Espírito Santo had the highest mortality, with the exception of 2021. In turn, Minas Gerais had the highest fatality rate throughout the analyzed pandemic period. The state of Espírito Santo had a higher incidence of COVID-19, as well as higher mortality, when compared to the state of Minas Gerais. In turn, Minas Gerais had a higher fatality rate. Furthermore, both states showed similar trends for mortality, lethality, and incidence in the years 2020 and 2021.

Metformin is an oral antidiabetic agent with antimicrobial properties, excreted in an active and unmetabolized form. Like some non-antibiotic drugs, subinhibitory concentrations of metformin may contribute to the expression of microbial resistance in wild-type strains. This work aimed to evaluate the biofilm formation of Pseudomonas aeruginosa TGC04 exposed to 100 and 200 µg/mL of metformin, varying the Chemical Oxygen Demand (COD) and flow regime. Biofilms were quantified after 2 and 24 hours, observing reductions and increases in biofilm growth around 13 and 64%, respectively. The greatest biofilm growth occurred in cells exposed to 200 µg/mL of metformin. Both the flow regime and COD concentration were important for the development of the biofilm, whose cells were mostly weakly to moderately adhered. The study provides evidence that in polluted aquatic systems with turbulent regimes, the inhibitory concentration of metformin promoted the least disturbances to the biofilm.

Vagueira Beach on the Central Portuguese coast, is known as one of the places in Europe most affected by coastal erosion. The area has suffered more than 156 meters of coastline retreat over the period 1958 to 2001. With the aim to evaluate the influence of local factors on coastal erosion, this paper assesses the anthropogenic and natural factors that are related with the retreat of the coastline, by adopting statistical correlation and regression analyses. Through the Pearson's correlation coefficient (r) it was observed that local factors such as annual dredging at the Aveiro Port entrance (r = 0.93), the total length of groins in the Espinho-Vagueira section (r = 0.89), and storm events (r = 0.52) are directly related to coastline retreat in the area. A multiple linear regression model was developed in which coastline retreat is explained by these same factors over the period 1980 to 2006. With a coefficient of determination of R² = 0.91, it was observed that length of groins (significant at the 1% level), dredging of the port entrance (significant at the 5% level) and precipitation (as a proxy for storm events; significant at the 10% level) are significantly correlated with coastline retreat. Hence, it is shown that anthropogenic factors are the main drivers of coastline retreat in Vagueira Beach. This study provides an innovative approach for the assessment of coastal erosion, resulting in important information that can be used for decision-making related to coastal zone management as it allows to understand in greater detail the main drivers of coastal erosion.

he paper offers an innovative cooking utensil design for remote, isolated, and even peri-urban communities at a low price, with high reliability and simple construction. It can alleviate energy poverty and improve food security. This utensil uses only local solar energy directly and allows comfortable indoor cooking. This paper provides the design principles of a solar cooker/frying pan or generic heater, based on a PV panel or a plurality of them, which are directly connected to a plurality of Positive Thermal Coefficient (PTC) resistors to match the power. PTCs are nowadays produced in massive quantities and are widely available at low cost. The proposed device does not require an electronic controller or a battery for its operation. The aim is for family use, although the design can be easily scaled to a larger size or power, maintaining its simplicity. Electric heating inside or attached to the cooking pot, plus the temperature self-limiting effect of PTCs, allows for thermally insulating the cooking pot from its outside using ordinary materials. Insulation en-hances energy efficiency during cooking and keeps cooked food warm for a long time. Clean development would receive a significant impulse with its application. A simple mathematical model describes its functioning and states guidelines for adequate design. The results indicate a successful proof of concept and high efficiency both for water and oil as representatives of cooking.

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.

Background: Visceral leishmaniasis affects approximately 12 million people worldwide. Current existing drugs cause several side effects and resistance, the identification of new therapeutic targets for the development of new drugs is necessary. The vesicular trafficking in the parasite flagellar pocket is essential for parasite survival and proliferation, but little is known about the proteins involved in the endocytic/secretory pathways. In this work, we are describing the characterization of a transporter cargo protein SFT-2/Got-1 like in Leishmania infantum. Material and Methods: Using bioinformatics tools, the putative Got-1 protein A4HSK3 was characterized structurally and phylogenetically. Molecular biology was used to clone and express the protein and confocal fluorescence to determine its subcellular localization. Results: The Got-1 like protein presents four alpha helix TM conserved domains (aa38-aa147) characteristics of the Got-1/SFT-2 family proteins and an important Pen-2 conserved motif LGDYXXF located in the extracellular loop. Confocal microscopy suggests that Got-1/SFT-2 like is localized in the flagellar pocket, and is partially co-localized with the L. infantum presenilin-like protein. Phylogenetically, the Leishmania sp Got-1 like is contained in a subgroup of proteins clearly detached from the other Trypanosomatidae, such as T. cruzi and T. brucei. Conclusions: Our data show the presence of an important transported proteins, and its colocalization with the presenilin aspartyl protease in the flagellar pocket of the L. infantum open new perspectives to identify novel targets, which can be an alternative therapeutic strategy against leishmaniasis.

Sewage sludge is an organic waste generated in waste-water treatment plants with certain content of nutrients, what may potentially be used as a source of slow release fertilizer, especially as phosphorus (P) source, but it demands some pre-treatment and the content of P is much lower compared to soluble mineral fertilizers. For these reasons, composted sewage sludge was used to manufacture pelletized organomineral fertilizers, mixing it with the inorganic sources monoammonium phosphate (MAP) and AshDec® (ASD) (thermochemically incinerated sewage sludge). The fertilizers were physiochemically characterized and evaluated as to the dynamics of soil P solubilization, and the forms of P remaining according to its lability. The sources evaluated were: organic compost of sewage sludge powder (SSC), pelletized SSC (SCP), pelletized organominerals SSC+MAP (S+MAP) and SSC+ASD (S+ASD), ASD alone, all compared to a soluble mineral fertilizer (MAP), and a control without P fertilizer. A test was conducted in leaching columns with 50 g of soil (Oxisol), where the fertilizers were applied at a dose of 100 mg P/column, and 30 mL of water or 2% citric acid were added daily for 30 consecutive days. The collected leachates had pH measured and P content determined. Pelletizing process resulted in denser products and promoted more gradual P release. The organomineral S+MAP was the most water-soluble recycled source, solubilizing about 70% of the total P, while the others presented much lower solubilization (&lt;20%). In contrast, all fertilizers showed high solubility in 2% citric acid (except for S+ASD). After leaching, the greatest amount of P remaining in the soil as labile and moderately labile. Composting and the AshDec process produced materials with slow P solubilization, which would be favoured to solubilize in acidic soils and acidic rhizosphere conditions. In turn, the organomineral mixture of SSC with a highly soluble mineral fertilizer (MAP) resulted in a promising product with intermediate nutrient solubility, better synchronized with crop demand, thus increasing efficiency in P use.

Land surface temperature (LST) is a key variable in surface-atmosphere energy and water exchanges. The main goals of this study are to (i) evaluate the LST of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and ERA5 reanalyses over Iberian Peninsula using the Satellite Application Facility on Land Surface Analysis (LSA-SAF) product and to (ii) understand the main drivers of the LST errors in the reanalysis. Simulations with the ECMWF land-surface model in offline mode (uncoupled) were carried out over the Iberian Peninsula and compared with the reanalysis data. Several sensitivity simulations were performed in a confined domain centered in Southern Portugal to investigate potential sources of the LST errors. The Copernicus Global Land Service (CGLS) fraction of green vegetation cover (FCover) and the European Space Agency’s Climate Change Initiative (ESA-CCI) Land Cover dataset were explored. We found a general underestimation of daytime LST and slightly overestimation at night-time. The results indicate that there is still room for improvement in the simulation of LST in ECMWF products. Still, ERA5 presents an overall higher quality product in relation to ERA-Interim. Our analysis suggested a relation between the large daytime cold bias and vegetation cover differences between (ERA5 and CGLS FCocver) with a correlation of -0.45. The replacement of the low and high vegetation cover by those of ESA-CCI provided an overall reduction of the large Tmax biases during summer. The increased vertical resolution of the soil at the surface, has a positive impact, but much smaller when compared with the vegetation changes. The sensitivity of the vegetation density parameter, that currently depends on the vegetation type, provided further proof for a needed revision of the vegetation in the model, as there is a reasonable correlation between this parameter and the Tmax mean errors when using the ESA-CCI vegetation cover (while the same correlation cannot be reproduced with the original model vegetation). Our results support the hypothesis that vegetation cover is one of the main drivers of the LST summertime cold bias in ERA5 over Iberian Peninsula.

Lignocellulosic fibers are widely applied as composite reinforcement due to their properties. The thermal degradation behavior determines the maximum temperature in which the fiber can be applied without significant mass loss. It is possible to determine these temperatures using Thermogravimetric Analysis (TG). In particular, when curves are obtained at different heating rates, kinetic parameters can be determined and more detailed characteristics of the material are obtained. However, every curve obtained at a distinct heating rate demands material, cost, and time. Methods to predict thermogravimetric curves can be very useful in the materials science field and in this sense mathematical approaches are powerful tools if well employed. For this reason, in the present study, curaua TG curves were obtained at three different heating rates (5, 10, 20, and 40 °C.min-1) and Vyazovkin kinetic parameters were obtained. After, the experimental curves were fitted using an artificial neural network (ANN) approach followed by a Surface Response Methodology (SRM). Curves at any heating rate between the minimum and maximum experimental heating rates were obtained with high reliability. Finally, Vyazovkin kinetic parameters were tested again with the new curves showing similar kinetic parameters from the experimental ones. In conclusion, due to the capability to learn from the own data, ANN combined with SRM seems to be an excellent alternative to predict TG curves that do not test experimentally, opening the range of applications.

A detailed structural investigation of a promising bio-based polymer, polyglycerol citrate poly-ester, obtained by bulk polycondensation of glycerol (Gly) against citric acid (Cit) under mild reaction was performed. This polymer was suggested to be well suited for coating seeds or similar agricultural applications. The reaction in conditions with and without catalyst use (sulfuric acid, H2SO4) was investigated, showing evidence that it is possible to modify the polymer solubility according to the ratio and catalyst utilization. 13C and 1H NMR indicated that synthesis catalyzed with Cit excess leads to higher esterification degrees of citrates groups. In contrast, the Gly moi-eties are more prominent in catalyzed polymers regardless of the excess monomers. Overall, a successful conversion of Gly and Cit into polyesters was attained, even without catalysis, enabling a simple route for large-scale production of this green material to be used as coating material. Tests on soybean seed coating with a PGCit solution of 75% indicated that the seed quality and ger-mination rate was not affected by PGCit coating, concluding that this polymer is promising for this application.

The soil-structure interaction represents an important parameter when analyzing the dynamic behavior of bridges, taking into account the integration between soil, foundation, and structure to ensure an adequate structural representation. In this paper, a computational modeling strategy using soil-structure interaction (SSI) methodology was applied to represent the dynamic behavior of a pedestrian bridge (LOP). The computational models were validated using monitoring results from an extensive structural health monitoring campaign. The bridge monitoring program was characterized using embedded sensors and cutting-edge technology for remote monitoring: ground-based radar interferometry and video motion amplification. The instrumentation results were compared to establish the capabilities and advantages of this novel remote monitoring technique. The experimental results obtained from free and forced vibrations in the asset served as a basis for validating the developed computational model and allowed evaluating the asset be-havior in service for different loading conditions. This paper emphasizes the SSI approach to represent the pedestrian bridge dynamic behavior more accurately, allowing computational models to represent the LOP structural responses over the course of its life-cycle.

There is a lack of information on vaccination for pregnant women in the Brazilian literature. Our aim was to evaluate the data on vaccines recorded on the pregnancy card and knowledge about the importance of vaccination for women admitted for labor in a reference public tertiary maternity unit in Presidente Prudente, São Paulo, Brazil. Vaccine data as prescribed by the National Immunization Program of Brazil (NIP) in prenatal cards for patients in labor from the 45 municipalities of the western region of São Paulo state were obtained. A questionnaire relating to knowledge about the types and importance of vaccination in pregnancy was applied. All vaccines indicated by the NIP were registered in only 12.0% of the prenatal cards, and 33.0% of cards registered any vaccines. In this group, 16.6% were aged between 14 and 21 years, and tetanus and COVID-19 were the most prevalent vaccines that they had heard of during prenatal care. Data on vaccines was poorly recorded in the cards, suggesting a lack of attention and unpreparedness of professionals working in primary care. Our study has countrywide and global relevance, and may be applied mainly in Latin American countries facing similar difficulties and limitations with low rates of vaccination during pregnancy.

The study presented here, through the use of GIS and physical variables, generate a new meth-odology for the calculation of erosivity (Factor R) for the qualitative evaluation of soil loss po-tential (laminar erosion) in the Northwest margin of the municipality of São Francisco, mostly located in the Pardo-MG river basin. The results obtained were statistically correct when com-pared to the traditional R calculation and the laminar erosion methodology. It is worth noting that the new proposal presented here indicated sites of qualitative loss of soil in the same places where there are closed-loop satellite signals of degraded Cerrado, something not identified in the traditional model. As conclusion it can be said that the obtained results were extremely sat-isfactory, being advised more studies to verify this new method proposed here in more places beyond the study area elaborated here

Multicriteria decision aid requires a database as a decision matrix, in which two or more alternatives are evaluated according to two or more variables selected as decision criteria. Several problems of this nature use measures by Likert scales. Depending on the method, parameters from these data (e.g. means, modes or medians) are required for calculations. This parameterization of data in ordinal scales has fueled controversy for decades between authors who favor mathematical/statistical rigor and argue against the procedure, stating that ordinal scales should not be parameterized, and scientists from other areas who have shown gains from the process that compensate for this relaxation. The aim of this article is to demonstrate the advantages of the Composition of Probabilistic Preferences (CPP) method in multicriteria problems with data from Likert scales. The CPP is capable of allaying the protests raised and obtaining more accurate results than descriptive statistics or parametric models can bring. The proposed algorithm in R-code involves the use of CPP with empirical distributions and fitting histograms of data measured by Likert scales. Two case studies with simulated datasets having peculiar characteristics and a real case illustrate the advantages of the CPP.

In this research, we present a comprehensive methodology to categorize perfumes based on their fragrance profiles and subsequently aid in creating innovative odoriferous molecules using advanced neural networks. Drawing from data on Parfumo and the Good Scents Company webpage (Parfumo, 2008; The Good Scents Company, 2021), the study employs sophisticated web scraping techniques to gather diverse perfume attributes. Following this, a k-means algorithm is applied for perfume clustering, paving the way for recommending similar scents to consumers. The process then bridges customer preferences to molecular design by incorporating their feedback into generating new molecules via graph neural networks (GNNs). Through converting the Simple Molecular Input Line Entry System (SMILES) representation into graph structures, the GNN facilitates the creation of new molecular designs attuned to consumer desires. The proposed approach offers promising avenues for consumers to pinpoint similar perfume choices, incorporating feedback, and for manufacturers to conceptualize new fragrant molecules with a high likelihood of market resonance.

With the rising trends in elderly populations around the world, there is a growing interest in understanding how climate sensitivity is related to their thermal perception. Therefore, we analyzed the associations between mortality in the elderly due to cardiovascular (CVD) and respiratory diseases (RD) and meteorological variables, for three cities in the State of São Paulo, Brazil: Campos do Jordão, Ribeirão Preto and Santos, from 1996 to 2017. We applied the Autoregressive Model Integrated with Moving Average (ARIMA) and the Principal Component Analysis (PCA) in order to evaluate statistical associations. Results showed CVD as a major cause of mortality, particularly in the cold period, when a high mortality rate is also observed due to RD. The mortality rate was higher in Campos do Jordão and lower in Santos (and intermediate values in Ribeirão Preto). Campos do Jordão results indicate an increased probability of mortality from CVD and RD due to lower temperatures. In Ribeirão Preto, the lower relative humidity may be related to the increase in CVD and RD deaths. This study emphasizes that, even among subtropical climates, there are significant differences. Therefore, this can assist decision makers in the implementation of mitigating and adaptive measures.

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region's climate has a significant impact on how water is managed and used, mostly in the primary sector (agroforestry systems, livestock, and agriculture), and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the S. Francisco River basin (SFRB) is assessed in three periods (1970−2000, 1981−2022) in the past and 20412060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot-summer (Csa) and warm-summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The Source and the mouth of SFRB are projected to endure the major impacts of climate change that is followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability, and quality for human use will all be impacted. Consequences on ecosystems, agricultural and for the socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating to a larger extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in the São Francisco River basin from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45%, and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$ 6,000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin's dispersed demographic and economic profile. To build routes towards a shared sustainable goal—namely, to adapt and reduce the expected climate change impacts in SFRB—it is imperative that integrated measures be conducted with the cooperation of stakeholders, local population, and decision-makers.

Introduction: Multiple sclerosis (MS) is a demyelinating, chronic, inflammatory and autoimmune disease of the central nervous system (CNS) with axonal degeneration, presenting a progressive and variable course. MS patients usually have complications, such as bladder dysfunction, presence of urinary symptoms and Urinary Tract infection (UTI), which is one of the three most common non-neurological complications in MS patients. Objective: Analyze the most diverse aspects of UTI in MS patients, focusing on risk factors, prevalence, hospitalization and mortality rates of UTIs in this group. Methods: A non-systematic review of articles published on PubMed in the last 10 years with the search terms "Urinary Tract Infection" AND "Multiple Sclerosis". Discussion: MS patients have a high UTI prevalence, mainly due to the occurrence of urinary disorders in these patients. The most common symptoms of UTI in MS patients are urinary urgency, polyuria, nocturia, urinary retention, and incontinence. Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae were the most found organisms and treatment is based on antibiotic therapy. Moreover, UTIs can precipitate outbreaks, worsen the disease, causing more damage and a severe neurological condition deterioration. Therefore, UTIs in this group are associated with a high hospitalizations rate and a high mortality rate. Conclusion: UTI represents a great risk and concern in MS patients. The high prevalence, hospitalization rate and mortality rate of UTI in MS is worrying, such as the cause-consequence relationship between UTIs and the use of corticosteroids in outbreaks. Therefore, it is important to be aware of a UTI in this group to make early diagnoses, adequate management, and new infections prevention. Thus, further studies are needed to thoroughly analyze each nuance of this important comorbidity for MS patients.

Aim: This study aimed to evaluate the sociodemographic, behavioral, and biological profile and its relationship with the emergence of chronic non-communicable diseases in riverside populations in the Xingu region, Pará, Brazil. Methods: Characteristics related to health indicators and which risk factors are considered most important were also analyzed. This is a cross-sectional, exploratory, and descriptive study. The sample consisted of riverside people over 18 years of both sexes. The sample size (n.86) was calculated with a confidence level of 95% and a sample error of 5%. To divide the groups, the K-means clustering algorithm was adopted through an unsupervised method and the values were expressed as median. For continuous and categorical data, the Mann-Whitney and Chi-square tests were used, respectively, and the significance level was set at p<5%. To classify the degree of importance of each variable, the multi-layer perceptron algorithm was applied. Results: Based on this information, the sample was divided into two groups: the group with low or no education, with bad habits and worse health conditions, and the group with opposite characteristics. The risk factors considered for cardiovascular diseases and diabetes in the groups were low education (p < 0.001), sedentary lifestyle (p < 0.01), smoking, alcoholism, body mass index (p < 0.05) and the waist-hip ratio, with values above the expected, in both groups. Conclusions: The factors considered important to have a good health condition or not were the educational and social conditions of these communities and a part of the riverside population was considered healthier than the other.

The reliability analysis allows to estimate the system's probability of detecting and identifying outlier. Failure to identify an outlier can jeopardise the reliability level of a system. Due to its importance, outliers must be appropriately treated to ensure the normal operation of a system. The system models are usually developed from certain constraints. Constraints play a central role in model precision and validity. In this work, we present a detailed optical investigation of the effects of the hard and soft constraints on the reliability of a measurement system model. Hard constraints represent a case in which there exist known functional relations between the unknown model parameters, whereas the soft constraints are employed for the case where such functional relations can slightly be violated depending on their uncertainty. The results highlighted that the success rate of identifying an outlier for the case of hard constraints is larger than soft constraints. This suggested that hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. After identifying and removing possible outliers, one should set up the soft constraints to propagate the uncertainties of the constraints during the data processing. This recommendation is valid for outlier detection and identification purpose.

Despite the acknowledged relevance of renewable energy sources, biofuel production supported by food-related agriculture has faced severe criticism. One way to minimize the considered negative impacts is the use of sources of non-food biomass or wastes. Synthetic biology (SB) embraces a promising complex of technologies for biofuel production from non-edible and sustainable raw materials. Therefore, it is pertinent to identify the global evolution of investments, concepts, and techniques underlying the field in support of policy formulations for sustainable bioenergy production. We mapped the SB scientific knowledge related to biofuels using software that combines information visualization methods, bibliometrics, and data mining algorithms. The United States and China have been the leading countries in developing SB technologies. Technical University of Denmark and Tsinghua University are the institutions with higher centrality and have played prominent roles besides UC-Los Angeles and Delft University Technology. We identified six knowledge clusters under the terms: versatile sugar dehydrogenase, redox balance principle, sesquiterpene production, Saccharomyces cerevisiae, recombinant xylose-fermenting strain, and Clostridium saccharoperbutylacetonicum N1-4. The emerging trends refer to specific microorganisms, processes, and products. Yarrowia lipolytica, Oleaginous yeast, E. coli, Klebsiella pneumoniae, Phaeodactylum tricornutum, and Microalgae are the most prominent microorganisms, mainly from the year 2016 onwards. Anaerobic digestion, synthetic promoters, and genetic analysis appear as the most relevant platforms of new processes. Improved biofuels, bioethanol, and N-butanol are at the frontier of the development of SB-derived products. Synthetic biology is a dynamic interdisciplinary field in environmentally friendly bioenergy production pushed by growing social concerns and the emergent bioeconomy.

The objective of this work was to investigate the deacidification of bio-oils (BOs) from triglyceride-based biomass through the application of liquid-liquid extraction (LLE) in a simple stage, using methanol and water as a binary solvent and feed/solvent ratio of 1/1. For this, the effects of process parameters such as the water content present in the solvent, the content of carboxylic acids present in the bio-oil, and the extraction temperature on the deacidification process through the efficiency and distribution coefficient were evaluated, as well as the effects of such parameters on the quality of deacidified bio-oils through physical-chemical analyzes and GC-MS analysis. The results show that such process parameters significantly affect the quality of deacidified bio-oils. The ideal condition to have the highest acid removal, i.e., the highest deacidification efficiency (72.65%), is the one in which the deacidification process is performed with aqueous methanol (5% water) at 35 °C and for BOs that have a total acid number (TAN) equal to 24.38 mg KOH/g. Therefore, the process of deacidification by LLE using aqueous methanol is a promising alternative for removing carboxylic acids and other oxygenated compounds, contributing significantly to the upgrading or improving biofuels produced by catalytic thermal cracking.

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal man-agement. This study aims to develop and to validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule formula implemented in GEE and is capable to determine the coastline retreat of a profile through the creation of a simple vector line from topo-bathymetric data. The model shows a very high cor-relation (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE platform seems to be an important tool for coastal management. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific commu-nity.

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence 15 of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal 16 management. This study aims to develop and to validate two different models to predict the 17 sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for plan-18 etary-scale environmental data analysis. The first model is a Bathtub Model based on the uncer-19 tainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and 20 Modeling System software. The validation process performed in the Rio Grande do Sul coastal 21 plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule for-22 mula implemented in GEE and is capable to determine the coastline retreat of a profile through the 23 creation of a simple vector line from topo-bathymetric data. The model shows a very high correla-24 tion (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE 25 platform seems to be an important tool for coastal management. The models developed have been 26 openly shared, enabling the continuous improvement of the code by the scientific community.

In this work, the cross-linked PMMA-based dental resins scraps were submitted to pyrolysis to recover MMA (Methylmethacrylate). The thermal degradation of cross-linked PMMA-based dental resins scraps was analyzed by TG/DTG to guide the operating conditions in pilot scale. The pyrolysis experiments carried out in a reactor of 143L, at 345, 405, and 420°C, 1.0 atmosphere. The reaction liquid products obtained at 345°C, physicochemical characterized for density, kinematic viscosity, and refractive index. The chemical composition of liquid products obtained at 345°C, 30, 40, 50, 60, 70, 80, and 110 minutes, at 405°C, 50, 70, and 130 minutes, and at 420°C, 40, 50, 80, 100, 110, and 130 minutes determined by GC-MS. The experiments show that liquid phase yields were 55.50%, 48.73%, and 48.20% (wt.), at 345, 405, and 420°C, respectively, showing a smooth sigmoid behavior, decreasing with increasing temperature, while that of gas phase were 31.69%, 36.60%, and 40.13% (wt.), respectively, increasing with temperature. The liquid products density, kinematic viscosity, and refractive index obtained at 30, 40, 50, 60, 70, 80, and 110 minutes, varied between 0.9227 and 0.9380 g/mL, 0.566 and 0.588 mm2/s, and 1.401 and 1.414, respectively, showing percentage deviations between 0.74 and 2.36%, 7.40 and 10.86%, and 0.00 and 0.92%, respectively, compared to standard values for density, kinematic viscosity, and refractive index of pure MMA at 20 °C. The GC-MS identified in the reaction liquid products at 345, 405, and 420°C, 1.0 atm, esters of carboxylic acids, alcohols, ketones, and aromatics, showing concentrations of MMA between 83.454 and 98.975% (area.). For all the depolymerization experiments, the concentrations of MMA in the liquid phase, between 30 and 80 minutes, reach purities above 98% (area.), decreasing drastically with increasing reaction time after 100 minutes, thus making it possible to depolymerize the cross-linked PMMA-based dental resins scraps by pyrolysis to recover MMA. The optimum operating conditions to achieve high MMA concentrations, as well as elevated yields of liquid reaction products were 345 °C and 80 minutes.

We show that low quality of all 427 Brazilian SARS-CoV-2 genomes recently published in Science (1) challenges their phylogenetic inference and may lead to incorrect typing of viral strains in clades with no statistical support. Absence of basecalling quality in genome assemblies and proper phylogeny parameter estimates preclude the assessment of signal-to-noise ratio in the data, downstream analysis and conclusions.

In precision agriculture in fertigated crops it is necessary to optimize the use of water and chemicals, and enable efficient application of fertilizers in order to ensure the best yield and avoid risks of soil salinization and contamination. In this study, an intelligent system was developed with the objective of monitoring, in real-time, moisture and solute concentrations in soil cultivated with lisianthus (Eustoma grandiflorum, var. Casablanca) fertigated under a protected environment. During one crop cycle, moisture was monitored in soil solution using TDR100 reflectometer and solute concentrations were monitored with ceramic cup extractors. Plants were fertigated with a solution containing five potassium concentrations (50, 100, 150, 200, and 250 mg dm-3) applied when the soil reached moisture limits of 0.20, 0.15, 0.13, 0.11, and 0.09 cm3 cm-3. Experimental plots were arranged in a randomized block design in a 5 x 5 factorial scheme (moisture limits x potassium concentrations in soil solution), with four replicates. The proposed intelligent system enabled precise monitoring of moisture and electrical conductivity by TDR, and potassium, and other solute concentrations with extractors, being indicated for the management of lisianthus fertigation under greenhouse conditions with greater environmental safety and reduction of water consumption and risk of salinization.

Several studies have already demonstrated the relationship between the loss of natural habitats and the incidence of diseases caused by vectors, such as dengue, which is an acute fever disease, considered a serious public health problem. The aim of the present study was to analyze the relationship between land use changes between 2009 and 2019 and the occurrence of dengue fever in 2015 and 2019 by municipality, using the state of Minas Gerais as a case study. For this, secondary data obtained from openly available sources were used. Natural vegetation cover data were obtained from the MAPBiomas platform and dengue occurrence data from the Ministry of Health, in addition to socioeconomic indicators from the Brazilian Institute for Geography and Statistics. Between 2015 and 2019, 1,255,731 cases of dengue were recorded throughout the state of Minas Gerais, ranging from 0 to 227 per thousand inhabitants between municipalities. The occurrence of dengue was distributed throughout all regions of Minas Gerais, affected by climatic and socioeconomic aspects. In general, municipalities with net loss of natural vegetation, predominantly located in the Cerrado biome, had the highest number of dengue cases in the studied period. Despite the significant positive relationship between these two variables, three of the eight socioeconomic parameters analyzed also affected the occurrence of dengue: population density, human development index (both positively) and Gini inequality index (negatively). These results indicate that, contrary to expectations, municipalities with better social conditions had more dengue cases. Our study indicates that natural vegetation is, directly or indirectly, involved in the ecosystem service of dengue control, despite the occurrence of this disease being affected by multiple factors that interact in a complex way. Thus, policies towards reducing deforestation must be complemented by a continuous investment in public health policies and reduction of social inequalities to efficiently control dengue fever.

The covid-19 pandemic has generated substantial changes in the lives of the population, such as increased physical inactivity, which can lead to overweight and, consequently, repercussions on glucose homeostasis. A population-based household epidemiological survey was conducted by stratified, multistage probability cluster sampling (October and December 2020) in Brazil. Participants were classified as physically active or inactive during leisure time according to the recommendations of the World Health Organization. HbA1c levels were categorized as normal (≤6.4%) or with glycemic changes (≥ 6.5%). The mediating variable was excess weight (overweight and obese). Multivariate logistic regression analyzes were performed to examine the association between physical inactivity and glycemic changes. Mediation was analyzed using the Karlson–Holm–Breen method to verify the influence of excess weight on the association. We interviewed 1,685 individuals, mostly women (52.4%), 35–59 years old (45.8%), race/ethnicity brown (48.1%), and excess weight (56.5%). The mean HbA1c was 5.68% (95% CI: 5.58-5.77). Individuals physically inactive were 2.62 times more likely to have glycemic alterations (OR:2.62.95% CI:1.29-5.33), and 26.87% of this association was mediated by excess weight (OR:1.30:95% CI:1.06-1.57). Physical inactivity in leisure time increases the chances of glycemic alterations, and part of this association can be explained by excess weight.

Angiogenesis is a hallmark of ovarian cancer (OC) it promotes rapid cell growth and the associated metastasis. Identifying new bioactive compounds to target angiogenesis may provide valuable paradigms as therapeutic strategies. Melatonin is a well-characterized indoleamine that possesses important anti-angiogenic properties in a set of aggressive solid tumors. Herein, we evaluated the role of melatonin therapy on the angiogenic signaling pathway in OC of an ethanol-preferring rat model that mimics the same pathophysiological conditions occurring in women. OC was chemically induced with a single injection of 7,12-dimethylbenz(a)anthracene (DMBA) under the ovarian bursa. After the rats developed serous papillary OC, half of the animals received i.p. injections of melatonin (200 µg/100 g body weight/day) for 60 days. Serum levels of melatonin were higher following therapy, and the expression of its receptor MT1R was significantly increased in OC-bearing rats, regardless of ethanol intake. TGFB1, a transforming growth factor-beta1, was reduced only after melatonin treatment. Importantly, vascular endothelial growth factor (VEGF) was severely reduced after melatonin therapy in animals given or not given ethanol. Conversely, the levels of VEGF receptor 1 (VEGFR1) was diminished after ethanol consumption, regardless of melatonin therapy, and VEGFR2 was only reduced following melatonin. Hypoxia-inducible factor (HIF)-1α was augmented with ethanol consumption, and notably, melatonin significantly reduced their levels. Collectively, our results suggest that melatonin attenuates angiogenesis in OC of an animal model of ethanol consumption; this provides a possible complementary therapeutic opportunity for concurrent OC chemotherapy.

In this paper we evaluate the effects of hard and soft constraints on the Iterative Data Snooping (IDS), an iterative outlier elimination procedure. Here, the measurements of a levelling geodetic network were classified according to the local redundancy and maximum absolute correlation between the outlier test statistics, referred to as clusters. We highlight that the larger the relaxation of the constraints, the higher the sensitivity indicators MDB (Minimal Detectable Bias) and MIB (Minimal Identifiable Bias) for both the clustering of measurements and the clustering of constraints. There are circumstances that increase the family-wise error rate (FWE) of the test statistics, increase the performance of the IDS. Under a scenario of soft constraints, one should set out at least three soft constraints in order to identify an outlier in the constraints. In general, hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. In that process, one should opt to set out the redundant hard constraints. After identifying and removing possible outliers, the soft constraints should be employed to propagate their uncertainties to the model parameters during the process of least-squares estimation.

Effectively responding to children’s nutritional status and eating behaviors in Mozambique requires a community-based care approach grounded in sound nursing research that is evidence-based. The Community Assessment, Intervention, and Empowerment Model (MAIEC) is a nursing theoretical model that bases clinical decision-making for community health nurses using communities as a unit of care. We used the MAIEC to identify a community-based nursing diagnosis to address children’s nutritional status and eating behaviors in Mozambique. Objectives: (1) To conduct a descriptive study of children’s nutritional status and eating behaviors in a school community in Mavalane, Mozambique, and (2) to identify a community-based nursing diagnosis using the MAIEC clinical decision-making matrix in the same school community. Method: A cross-sectional, quantitative study was conducted to assess the nutritional status of children using anthropometric data, including brachial perimeter and the tricipital skinfold, and standard deviation for the relation of weight-height, in a sample of 227 children. To assess community management of the problem and identify a community-based nursing diagnosis, we surveyed 176 parents/guardians and 49 education professionals, using a questionnaire based on the MAIEC clinical decision matrix as a reference. Results: Malnutrition was identified in more than half of the children (51.3%). We also identified a community-based nursing diagnosis of impaired community management related to the promotion of child health and healthy eating as evident by lack of community leadership, participation, and processing among more than 70% of the community members (parents/guardians and education professionals). Conclusion: A nursing diagnosis and diagnostic criteria for nutritional status and community management were identified. The need to intervene using a multidisciplinary public health approach is imperative, with the school community as the unit of care. In addition, reliable anthropometric data were used to complement the nursing diagnosis and guide future public health interventions.

We analyzed the interaction of two acceptor materials, reduced graphene oxide (RGO) and [6,6]-phenyl-C6-butyric acid methyl ester (PCBM), and poly(3-hexylthiphene) (P3HT), as well as the dependence of its photophysical properties with the temperature in the range 90 to 300 K. The nanocomposite of the films was analyzed by optical absorption ultraviolet-visible (UV-Vis) and photoluminescence (PL) and emission ellipsometry (EE) in a function of sample temperature. The surface morphology was studied by atomic force microscopy (AFM). We noted that onset levels (Eonset) of the nanocomposite of P3HT and RGO is smaller than the others. The PL spectra showed the presence of anomalies in the emission intensities in the nanocomposite of P3HT and PCBM. It was also possible to determine the electron-phonon coupling by calculating the Huang-Hys parameters and its dependence with the sample’s temperature. Through EE it was possible to analyze the degree of polarization and the anisotropy. We observed a high degree of polarized emission of the P3HT films which varies subtly according to the temperature. For nanocomposites with RGO the polarization degree in the emission decreases and the roughness on the surface increases. As a result, the RGO improves the energy transfer between adjacent polymer chains at the cost of greater surface roughness. Then, the greater energy transfer may favor applications of this type nanocomposite in OPVC's with enhancement in energy conversion efficiency.

Ruminal microorganisms play a pivotal role in cattle nutrition. The discovery of the main microbes responsible for enhancing the gain of weight in beef cattle might be used in therapeutic approaches to increase animal performance and cause less environmental damages. Here, we examined differences in bacterial and fungal composition of rumen samples of Braford heifers raised in a natural grassland from Pampa Biome in Brazil. We aimed to detect microbial patterns in the rumen that could be correlated with the gain of weight. 16S and ITS1 genes were amplified from ruminal samples and sequenced to identify the closest microbial relatives within the microbial communities. A predictive model based on microbes responsible for the gain of weight was build and further tested using the entire dataset. The model detected a set of microorganisms associated with animals in the high gain of weight group, including the bacterial taxa RFN20, Prevotella, Anaeroplasma and RF16 and the fungal taxa Aureobasidium, Cryptococcus, Sarocladium, Pleosporales and Tremellales. Most of these organisms have been correlated to the production of substances that improve the ruminal digestion process. These findings provide new insights about cattle nutrition and suggest the use of these microbes to improve beef cattle breeding.