The main goal of the paper is to compare the effects of the wave spectrum, computed using the Discrete Interaction Approximation (DIA) and the Webb–Resio–Tracy (WRT) methods, on statistical wave properties such as skewness and kurtosis. The statistical properties are obtained by integrating the three-dimensional free-surface Euler equations with a high-order spectral method combined with a phenomenological filter to account for the energy dissipation due to breaking waves. In addition, we investigate the minimum spatial domain size required to obtain meaningful statistical wave properties. The numerical simulations are performed over a physical domain of size 4.13 km × 4.13 km. The results indicate that statistical properties must be computed over an area of at least 4 km2. The results also suggest that selecting a more computationally expensive WRT method does not affect the statistical values to a great extent. The most noticeable effect is due to the energy dissipation filter that is applied. It is concluded that selecting the WRT or the DIA algorithm for computing the wave spectrum needed for the numerical simulations does not lead to major differences in the statistical wave properties. However, more accurate energy dissipation mechanisms due to wave breaking are needed.

The use of convolutional neural networks (CNNs) in image classification has become the standard method of approaching computer vision problems. Here we apply pre-trained networks to classify images of non-breaking, plunging and spilling breaking waves. The CNNs are used as basic feature extractors and a classifier is then trained on top of these networks. The dynamic nature of breaking waves is exploited by using image sequences to gain extra information and improve the classification results. We also see improved classification performance in using pre-computed image features such as the optical flow between image pairs. The inclusion of the dynamic information improves the classification between breaking wave classes. We also provide corrections to the methodology from the article from which the data originates to achieve a more accurate assessment of performance.

We introduce poly-symplectic extension of Souriau Lie groups Thermodynamics based on higher-order model of statistical physics introduced by R.S. Ingarden. This extended model could be used for small data analytics and Machine Learning on Lie groups. Souriau Geometric Theory of Heat is well adapted to describe density of probability (Maximum Entropy Gibbs density) of data living on groups or on homogeneous manifolds. For Small Data Analytics (Rarified Gases , sparse statistical survey,…), density of maximum entropy should consider Higher Order Moments constraints (Gibbs density is not only defined by first moment but fluctuations request 2nd order and higher moments) as introduced by R.S. Ingarden. We use Poly-sympletic model introduced by Christian Günther, replacing the symplectic form by a vector-valued form. The poly-symplectic approach generalizes the Noether theorem, the existence of momentum mappings, the Lie algebra structure of the space of currents, the (non-)equivariant cohomology and the classification of G-homogeneous systems. The formalism is covariant, i.e. no special coordinates or coordinate systems on the parameter space are used to construct the Hamiltonian equations. We underline the contextures of these models, and the process to build these generic structures.

This paper presents some results from a computational fluid dynamics (CFD) model of a multi-megawatt crosswind kite spinning on a circular path in a straight downwind configuration. The unsteady Reynolds averaged Navier-Stokes equations closed by the k−ω SST turbulence model are solved in the three-dimensional space using ANSYS Fluent. The flow behaviour is examined at the rotation plane, and the overall (or global) induction factor is obtained by getting the weighted average of induction factors on multiple annuli over the swept area. The wake flow behaviour is also discussed in some details using velocity and pressure contour plots. In addition to the CFD model, an analytical model for calculating the average flow velocity and radii of the annular wake downstream of the kite is developed. The model is formulated based on the widely-used Jensen’s model (Technical Report Risø-M; No. 2411, 1983), which was developed for conventional wind turbines, and thus has a simple form. Expressions for the dimensionless wake flow velocity and wake radii are obtained by assuming self-similarity of flow velocity and linear wake expansion. Comparisons are made between numerical results from the analytical model and those from the CFD simulation. The level of agreement was found to be reasonably good. Such computational and analytical models are indispensable for kite farm layout design and optimization, where aerodynamic interactions between kites should be considered.

Public health suffers from noxious gas of beached Sargassum algae. Floating barrages containing them at sea will be useful provided efficiently catch them and resist to hydrodynamic pressure. Nowadays design and installation of algae barrages are empiric. Structural break, anchor and mooring chain drifts can arise. We provide a mechanical model to evaluate stresses and loads on a structure made of nets and moorings. Hydrodynamic uncertainties occur through catches, fouling, and a range of sea currents appearing in lagoons or sheltered bays. We consider a nonlinear finite-element model of elastic membrane in large displacements and small strains. We study some forcings fixed a priori on a standard section of barrage. A section 50 m long, 1 m high, with two net-faces is examined at low and moderate current velocities, 0.05 and 0.35 m.s-1, while assuming specific vertical and horizontal catch pressures. A barrage installed in lagoon at Le François on Martinique Island and being observable by satellite imagery could benefit of the computed net and mooring tensions.

The seeds of red clover are heteromorphic and two color morphs can be visually recognized, light purple and yellow, resulting from heterozygosity and recessive homozygosity at two loci. Here, we report the responses of seed imbibition, seed germination, and early seedling growth of the two morphs to distilled water, sodium chloride, and complete nutrient solution. The sensitivity of red clover seeds to treatments increased with the stage of development in what seems to be a cumulative process. No differences were found in seed imbibition between morphs or between treatments. In seedling growth, on the contrary, treatments were always effective, but differences between morphs were only observed in seeds that were treated with nutrient solution, whereas in the intermediate stage of seed germination, the effects by treatments were observed together with the appearance of differences between morphs in distilled water and in the treatment by sodium chloride solution. Simultaneously, the superior performance of the yellow morph that was found in germination, which appears to be a trait stable across cultivars of red clover seeds, turned into a superior performance of the light purple morph in seedling growth.

Multispectral and 3D LiDAR remote sensing data sources are valuable tools for characterizing the 3D vegetation structure and thus understanding the relationship between forest structure, biodiversity and microclimate. This study focuses on mapping riparian forest species in the canopy strata using a fusion of Airborne LiDAR data and multispectral multi-sources and multi-resolution satellite imagery; Sentinel-2 and Pleiades at tree level. The idea is to assess the contribution of each data source in the tree species classification at the considered level. The data fusion was processed at feature-level and decision level. At feature level, LiDAR 2D attributes were derived and combined with vegetation indices. At decision level, LiDAR data was used for 3D tree crown delimitation providing unique trees or groups of trees that are used as a support for the species classification. Data augmentation techniques were used to improve the training process. Best results were obtained by the fusion of Sentinel-2 time series and LiDAR data with a Kappa of 0.66 thanks to red-edge based indices that better discriminate vegetation species and the temporal resolution of Sentinel-2 images that allows monitoring the phenological stages helping to discriminate the species.

Spatial light modulators (SLMs) have been widely used to achieve dynamic control of optical traps. Often, holographic optical tweezers have been presumed to provide nanometer or sub-nanometer positioning accuracy. It is known that some features concerning the digitalized structure of SLMs cause a loss in steering efficiency of the optical trap, but their effect on trap positioning accuracy has been scarcely analyzed. On the one hand, the SLM look-up-table, which we found to depend on laser power, produces positioning deviations when the trap is moved at the micron scale. On the other hand, phase quantization, which makes linear phase gratings become phase staircase profiles, leads to unexpected local errors in the steering angle. We have tracked optically-trapped microspheres with sub-nanometer accuracy to study the effects on trap positioning, which can be as high as 2 nm in certain cases. We have also implemented a correction strategy that enabled the reduction of errors down to 0.3 nm.

Motivated by diffraction experiments on the $\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$ reconstructed Si(111) due to deposition of rare earth elements (Dy, Tb) and silicide formation we analyse the splitting and non-splitting of superstructure spots. For this purpose, we model diffraction patterns for one dimensional structures generated by the binary surface technique and use supercell models to keep the analysis simple. Diffraction pattern are calculated in the framework of the kinematical diffraction theory and they are analyzed as a function of the domains and domain boundaries. Basic properties of the diffraction pattern are analyzed for model systems of a two-fold and a three-fold periodicity. The rules derived from these calculations are applied to the "real-world" system of Si(111)-($\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$)-RESi$2_{}$ (RE = Dy or Tb). Depending on the combination of domains and domain boundaries of different types a plethora of different features are observed in the diffraction patterns. These are analyzed to determine the sizes of both domain boundaries and domains from experimentally observed splitting of specific superstructure spots.

Familial Alzheimer’s disease (FAD) can be caused by mutations in PSEN1 that encodes presenilin-1, a component of the gamma-secretase complex that cleaves amyloid precursor protein. Alterations in calcium (Ca2+) homeostasis and glutamate signaling are implicated in the pathogenesis of FAD, however it has been difficult to assess in humans whether or not these phenotypes are the result of amyloid or tau pathology. This study aimed to assess early calcium and glutamate phenotypes of FAD by measuring the Ca2+ response of induced pluripotent stem cell (iPSC)-derived neurons bearing PSEN1 mutations to glutamate and the ionotropic glutamate receptor agonists NMDA, AMPA and kainate compared to isogenic control and healthy lines. The data shows that in early neurons, even in the absence of amyloid and tau phenotypes, FAD neurons exhibit increased Ca2+ responses to glutamate and AMPA, but not NMDA or kainate. Together this suggests that PSEN1 mutations alter Ca2+ and glutamate signaling as an early phenotype of FAD.

This study aims to analyze the interconnection between the concepts of digital economy and sustainability. These concepts have become popular due to awareness of climate change and increased development and adoption of technologies. Researchers, business leaders and policymakers are exploring the many ways digital technologies can be used to address sustainability issues. Using a systematic literature review with a bibliometric analysis, we examined a sample of 92 studies indexed in SCOPUS to identify research activity on this topic through April 2023. We found that 2022 had the highest number of peer-reviewed papers on the subject, with 31 publications. During the research, we also identified multiple opportunities for this interconnection, such as developing renewable energy and sustainable technological solutions, smart cities and sustainable urbanization, and sustainable consumption. These opportunities enabled by digital technologies allow companies to adopt sustainable business strategies and develop sustainable products. Despite these opportunities, the digital economy presents several challenges that can hinder efforts to achieve sustainability goals, such as increased e-waste, high energy consumption and rising carbon emissions, digital divide, job insecurity, growing monopolies, and data protection. These issues must be addressed to enable optimal use of the opportunities presented in the digital economy to promote sustainability.

Defect detection and identification from fruits and vegetables are particularly challenging for Indian agriculture. Defect Detection is a process to identify the defects or damages in vegetables and fruits, based on the shapes, colors and textures. The local market finds it difficult to cope with the defects and other infections in fruits and vegetables as quality evaluations and classification of vegetables and fruits have become tedious process. Recently, several approaches based on Image processing, Machine Learning and Artificial Intelligence methods have been proposed for the purpose of defect detection. On the basis of classifying the types of defects, related pathogens, and physical and morphological characteristics descriptors, we review the different approaches based on a corpus of 57 articles between 2016 and 2021. In the process of describing the defect analysis, steps from the target articles, algorithms, and methods including qualitative and quantitative evaluation are mainly summarized. The aim of this current review work is to present-day novel images and collects recent defective area calculation methods to detect surface defects of fruits and vegetables using RGB images and to classify whether the fruit is defected or fresh. A rigorous evaluation of many new algorithms provided for quality assurance by researcher’s probes of vegetables and fruits have been conducted in this work. This review work conveys that using the recent identification features will help to decrease the disadvantages in fruit storeroom owing to storage of the affected vegetables and fruits, ie. Preventing the spread of defects and other infections from the infected fruits and vegetables to the fresh ones.

The fourth industrial revolution, also known as Industry 4.0, has led to an increased transition towards automation and reliance on data-driven innovations and strategies. Companies in the manufacturing sector are heavily integrating Industry 4.0 technologies, including cloud compu-ting, cyber-physical systems (CPS), big data analytics, horizontal and vertical system integration, the internet of things (IoT), and additive manufacturing (3d printing). The interconnected systems and processes have significantly increased operational efficiency, enhanced organizational capacity to monitor and control functions, reduced costs, and improved product quality. One significant way that companies have achieved these benefits is by integrating diverse sensor technologies within these innovations, allowing critical data collection on products, equipment performance, and maintenance. The sensors connect systems and machines, allowing them to communicate and track operations for enhanced operations. While numerous research has been conducted to show the role of sensors in industry 4.0, limited studies show how these innovations can leverage product design to maximize benefits and opportunities. Given the rapidly changing market conditions, Industry 4.0 requires new products and business models to ensure companies adjust to the current and future changes. These requirements call for the evolutions in product design processes to accommodate design features and principles applicable in the current dynamic business environment. This research paper employs a systematic bibliometric literature review (LRSB) methodology to explore and synthesize data on how Industry 4.0 and sensors can leverage product design. The results show that various product design features create opportunities to be leveraged to guarantee the success of Industry 4.0 and sensor technologies. However, the research also identifies numerous challenges that undermine the ongoing transition towards intelligent factories and products.

The digital transition processes have demonstrated an enormous capacity to develop and implement sustainable solutions, which allow solving several problems such as poverty, high rates of species extinction and lack of equal opportunity. However, little attention is paid to the connection between the digital transition and sustainability. Thus, a systematic review of the bibliometric literature was developed to fill this knowledge gap and demonstrate the potential contributions of the digital transition to environmental, economic and social sustainability aspects. In environmental sustainability, the digital transition involves the application of technologies such as AI, big data analytics, IoT, and mobile technologies that are used to develop and implement sustainability solutions in areas such as sustainable urban development, sustainable production and pollution control. In economic sustainability, emerging digital technologies can drive transformation into the more sustainable circular economy, the digital sharing economy, and establish sustainable manufacturing and infrastructure design. In the digital transition to social sustainability, the studies analyzed demonstrate the need for multidimensional policy perspectives to address the current digital divide. For effective management of the digital transition that achieves sustainability goals, the study discusses alternative approaches that include innovation through experimentation, and dynamic and sustainable advantages achievable through temporary benefits.

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

A new research stream emerged in the 2000s dedicated to flexible work arrangements in public and private organizations, called “new ways of working” (NWW). This article aims to examine NWW from both a theoretical and empirical perspective, focusing on outcomes of this new concept and the debate between “mutual gains” vs. “conflicting outcomes.” Through a literature review, it examines this research field’s innovation and its rather vague theoretical foundations. Findings demonstrate that NWW definitions are diverse and somewhat imprecise, leading to fragmented research designs and findings; the research stream’s theoretical foundations should be better addressed. Findings also highlight the current lack of empirical data, which therefore does not allow any real conclusions on NWW’s effects on employees’ and organizations’ well-being and performance.

Automated vehicles (AVs), which are expected to enter the market within the near future, represent the current frontiers in mobility and urban planning. AVs are assumed to bring substantial benefits to cities in many aspects. The present study attempts to investigate this broad assumption by conducting a literature review on the possible implications of AVs in cities as well as synthesizing the current state of practice of AV pilots to detect trends in their deployment. In this paper, literature findings on AVs’ implication on vehicle ownership, mobility, land use as well thirteen uses cases were synthesized to capture the big picture of them in cities. The findings showed that, in the AV pilots, the operation of AVs is limited to routes stretching less than 3.5km and an operation speed of less than 18km/h; low speed has been one of the main concerns of the participating passengers to use them for daily trips. The results also revealed that although shared AVs are expected in urban mobility, private ownership will stay competitive since vehicle ownership has been a socio-cultural identity in the history of automobiles. The findings also underlined that the potential influence of AVs on active mobility is still unclear as the AVs have not been introduced on a larger scale. Regarding AVs’ impact on land use, their introduction results in the effective use of space, but they will cause suburbanization in the long term.

This paper generalizes the actuator disc theory to the application of crosswind kite power systems. For simplicity, it is assumed that the kite sweeps an annulus in the air, perpendicular to the wind direction (i.e. straight downwind configuration with tether parallel to the wind). It is further assumed that the wind flow has a uniform distribution. Expressions for power harvested by the kite is obtained, where the effect of the kite on slowing down the wind (i.e. the induction factor) is taken into account. It is shown that although the induction factor may be small for a crosswind kite (of the order of a few percentage points), neglecting it in calculations may result in noticeable overestimation of the amount of power harvestable by a crosswind kite system.

Industry 4.0 or the Fourth Industrial Revolution is driven by innovative technologies that have profound effects on both production systems and business models. This revolution is characterized by the addition of disruptive technologies and methods. These aspects of Industry 4.0 have a significant impact on marketing and have led to an evolution to ensure that marketing activities align with technological advancements and address consumers' current needs. The purpose of this paper is to formulate and discuss future research avenues for marketing considering the changes brought by Industry 4.0. The approach taken in the paper is to review the relevant literature and focus on the key themes most important for future research on industry 4.0 and marketing. Therefore, a systematic literature review was conducted based on SCOPUS indexing online database of scientific articles, the most important peer-reviewed peer in the academic world. The paper finds that there are a number of research avenues for marketing researchers to conduct investigations on, but the most important areas are five marketing principles in Industry 4.0: cooperation, conversation, co-creation, cognitivity, and connectivity.

In this work we present a new unsupervised and language-independent methodology to detect relations of textual generality, for this, we introduce a particular case of textual entailment (TE), namely Textual Entailment by Generality (TEG). TE aims to capture primary semantic inference needs across applications in Natural Language Processing (NLP). Since 2005, in the TE recognition (RTE) task, systems are asked to automatically judge whether the meaning of a portion of the text, the Text - T, entails the meaning of another text, the Hypothesis - H. Several novel approaches and improvements in TE technologies demonstrated in RTE Challenges are signalling of renewed interest towards a more in-depth and better understanding of the core phenomena involved in TE. In line with this direction, in this work, we focus on a particular case of entailment, entailment by generality, to detect relations of textual generality. In-text, there are different kinds of entailment, yielded from different types of implicative reasoning (lexical, syntactical, common sense based), but here we focus just on TEG, which can be defined as an entailment from a specific statement towards a relatively more general one. Therefore, we have T→GH whenever the premise T entails the hypothesis H, being it also more general than the premise. We propose an unsupervised and language-independent method to recognize TEGs, from a pair ⟨T,H⟩ having an entailment relation. To this end, we introduce an Informative Asymmetric Measure (IAM) called Simplified Asymmetric InfoSimba (AISs), which we combine with different Asymmetric Association Measures (AAM). In this work, we hypothesize the existence of a particular mode of TE, namely TEG. Thus, the main contribution of our study is to highlight the importance of this inference mechanism. Consequently, the new annotation data seems to be a valuable resource for the community.

Digital twins are gaining in popularity for simulating complex natural and urban environments. In this context, accurate segmentation of objects within 3D urban environments is of crucial importance. The aim of this project is to develop a methodology for extracting buildings from textured 3D meshes. To this end, PicassoNet-II, a semantic segmentation architecture is employed. The methodology also incorporates Markov field-based contextual analysis to assess post-segmentation features. In addition, building instantiation is performed using cluster analysis algorithms. Training this model to fit various datasets requires a large amount of annotated data, both from Quebec City, Canada, and from simulated data. Experimental results show that the use of simulated data improves segmentation accuracy, and the DBScan algorithm proves effective in extracting isolated buildings. This project paves the way for improved applications in 3D urban modeling, offering opportunities in fields ranging from urban planning to resource management. The positive results with simulated data reinforce the impact of this research on improving digital models of our ever-changing urban environments.

An effective process monitoring strategy is a requirement for meeting the challenges posed by increasingly complex products and manufacturing processes. To address these needs, this study investigates a comprehensive scheme based on classical machine learning methods, deep learning algorithms, and feature extraction and selection techniques. In a first step, a novel deep learning architecture based on convolutional neural networks (CNN) and gated recurrent units (GRU) is introduced to predict the local weld quality based on mid-wave infrared (MWIR) and near-infrared (NIR) image data. The developed technology is used to discover critical welding defects including lack of fusion (false friends), sagging and lack of penetration, and geometric deviations of the weld seam. Additional work is conducted to investigate the significance of various geometrical, statistical, and spatio-temporal features extracted from the keyhole and weld pool regions. Furthermore, the performance of the proposed deep learning architecture is compared to that of classical supervised machine learning algorithms, such as multi-layer perceptron (MLP), logistic regression (LogReg), support vector machines (SVM), decision trees (DT), random forest (RF) and k-Nearest Neighbors (kNN). Optimal hyperparameters for each algorithm are determined by an extensive grid search. Ultimately, the three best classification models are combined into an ensemble classifier that yields the highest detection rates and achieves the most robust estimation of welding defects among all classifiers studied, which is validated on previously unknown welding trials.

This paper explores the emergence of Sustainability-Linked Bonds (SLBs) as an innovative instrument to finance sustainability objectives. SLBs have emerged as a transformative financial instrument, establishing an explicit link between cost of funding and sustainability objectives. SLBs were first launched in 2019 and represent 7% of labelled bonds, still dominated by the more established green bonds. Issuance of SLBs now exceeds $250 billion. Following initial enthusiasm, they are now facing criticism. In the context of the growth of sustainable finance and concerns of greenwashing, this paper investigates ways to enhance the design of SLBs. Drawing on literature and expert interviews, the findings highlight the strong potential of SLBs to contribute to sustainability financing, especially in hard-to-abate sectors. The paper identifies the key positive attributes of SLBs and their limitations in five areas: key performance indicators’ (KPI) selection, sustainability performance targets’ (SPT) calibration, bond characteristics, reporting practices, and resource requirements. Recommendations to financial intermediaries, issuers and policy makers include defining standardized KPIs based on a materiality assessment, requesting SPTs to be supported by science and in line with an issuer’s core strategy, tailored step-up mechanisms and avoidance of call loopholes, and stricter reporting. SLBs represent an opportunity to add rigor to sustainable finance and better price externalities, where material topics have an explicit impact on cost of funding and credit ratings.

This article explores the relationship between green energy and cryptocurrencies in the sustainable energy finance sector. The research findings contribute to our understanding of the application of green economy practice, enabling investors in financial markets, policymakers, and stakeholders to make informed decisions and develop specific strategies. Adopting the green economy paradigm makes it possible to promote collaboration and innovation by integrating ethical and responsible principles that can improve the overall quality of processes and boost sustainable growth. Cryptocurrencies have been widely used as financial instruments over the last decade. Given the development of the cryptocurrency market and the growing awareness of greener and more energy-efficient tokens, the green economy has become a popular topic for understanding economic and political issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green energies. Therefore, this study examines the long- and short-term relationships between dirty cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), clean cryptocurrencies such as Cardano (ADA), Ripple (XRP), Stellar (XLM), and green energies such as ISE Clean Edge Global Wind Energy, S&P Global Clean Energy, S&P TSX Renewable Energy and Clean Technology, Solactive China Clean Energy, in the period from January 2020 to September 2023. The results show that diversification is key, with clean cryptocurrencies such as ADA, XLM and XRP offering diversification opportunities alongside "dirty" cryptocurrencies such as BTC and ETH. Although sustainable energy indices show mixed evidence in the long and short term, they remain relevant for those who focus on clean energy investments. It is also becoming increasingly relevant for investors in sustainable portfolios to assess their environmental impact, especially for energy-intensive cryptocurrencies, and it is advisable to explore sustainable blockchain technologies.

There is growing recognition of the adverse effects of body image dissatisfaction (BID) and eating disorder (ED) symptoms on adolescent health. The aim of this study was to estimate the prevalence of ED symptoms, BID, and their relationship in adolescents from public schools in Southern Brazil. A total of 782 schoolchildren (male: n=420, female: n=362); age: 15 ± 0,4 years) answered a self-administrated questionnaire to identify sociodemographic data. Children´s Figure Rating Scale was adopted to identify body image and Eating Attitudes Test (EAT-26) was applied to investigate ED symptoms. Inferential statistics and hierarchical model-controlled logistic regression were used for association between variables. Most of the schoolchildren reported being satisfied with their bodies. However, we observed a higher prevalence of dissatisfaction among girls for being overweight and thinness among boys. Female students and students from schools located in the central area of the city showed higher chances of developing ED symptoms, and the absence of symptoms of ED appeared to act as a protective factor against BID in schoolchildren. Results of this study show the need to reflect on these factors that influence the development of ED and non-acceptance of their own body in a population concerned with their physical appearance.

The initial development of seahorse juveniles is characterized by low digestion capabilities. Stable isotope analysis is an effective tool in studies of trophic food webs and animal feeding patterns. The present study provides new insights for the understanding of growth and food assimilation in early developing seahorses following a laboratory diet switch. The study was performed in early life stages of the seahorse Hippocampus reidi by assessing the influence of diet shift on changes and turnovers in carbon (δ13C) and nitrogen (δ15N) stable isotope in juveniles. Newborn seahorses were fed for 60 days following two feeding schedules (A6 and A11) based initially on copepods Acartia tonsa and subsequently on Artemia nauplii (since days 6 and 11, respectively). After prey shift, we determined δ13C and δ15N turnover rates as functions of change in either body mass (fitting model G) and days of development (fitting model D), contributions of metabolism and growth to those turnover rates, and diet-tissue discrimination factors. Survival, final dry weight and final standard length for diet A11 were higher compared to diet A6. The shift from copepods to Artemia lead to fast initial enrichments in δ13C and δ15N. Afterwards, the enrichment was gradually reduced until reaching the isotopic equilibrium with diet. In most cases, both fitting models performed similarly. The isotopic analysis revealed that 100% of tissue turnover was attributed to growth in diet A11, whereas 19-25% was endorsed to metabolism in diet A6. Diet-tissue discrimination factors were estimated for the first time in seahorse juveniles, resulting in higher estimates for diet A11 (2.9 ± 0.7‰ for δ13C; 2.5 ± 0.2‰ for δ15N) than in diet A6 (1.8 ± 0.1‰ for δ13C; 1.9 ± 0.1‰ for δ15N). This study highlights the relevance of feeding on copepods and their effect on isotopic patterns and discrimination factors in seahorse juveniles after a dietary shift. Regarding the application of the results achieved to feeding schedules in the rearing of H. reidi, a long period of feeding on copepods during the first days of development is highly recommended.

The marketing industry is rapidly evolving, necessitating educational programs to adapt and equip graduates with relevant skills and knowledge. This systematic literature review with bibliometric analysis (SLRBA) explores the integration of Problem-Based Learning (PBL) in marketing education. PBL is an instructional strategy that empowers students to solve real-life problems by integrating theory and practice, thus fostering critical thinking and decision-making skills. Our review synthesizes data from 71 sources, highlighting the definition of PBL, strategies to promote its implementation in marketing education, and the benefits and challenges associated with this approach. The findings indicate that PBL enhances student engagement, provides hands-on experience, and prepares students for real-world marketing challenges. Strategies such as using social media, serious games, e-learning, and feedback mechanisms are discussed for their effectiveness in promoting active learning and student participation. Despite its advantages, PBL faces challenges such as resource intensiveness, student resistance, and information integrity issues. This review underscores the importance of PBL in bridging the gap between theoretical knowledge and practical application, ultimately preparing marketing students to meet the demands of the industry. The paper concludes with recommendations for future research and best practices for implementing PBL in marketing education.

This study aims to determine the role of Industry 4.0 sensors in digital transformation. Using a systematic literature review with a bibliometric analysis, we examine a sample of 52 studies from the SCOPUS database to identify research activity on this topic until December 2022. We find that 2022 was the year with the highest number of peer-reviewed documents on the subject, with 18 publications. We also examine current themes and find that sensors can connect multiple systems and devices, thus enabling machine-to-machine communication and facilitating great precision during product designing, development, and production, thus enabling customization and improving quality. However, despite these benefits, the current sensor technologies face multiple challenges that undermine their maximum adoption.

The term fuzzy refers to things that are unclear or vague. In the real world, we often encounter a situation where we cannot determine whether the state is true or false, and fuzzy logic allows for more flexible reasoning. This is a form of multivalued logic where the truth values ​​of variables can be any real number between 0 and 1, as opposed to Boolean logic where the logical values ​​can only be 0 or 1. Fuzzy logic is therefore a problem-solving technique used to evaluate all available information and thus make the best decisions. When applied to marketing, fuzzy logic allows treating customers in an individual and personalized way, instead of being fully identified within a particular market segment. Fuzzy marketing considers the degree to which a customer belongs to certain segments and subsequently allows them to be targeted with messages that engage them emotionally. To better understand the application and importance of fuzzy logic in marketing strategy, we developed a systematic review of the bibliometric literature (LRSB). It was possible to create a connection between these concepts, marketing and fuzzy logic, to increase the efforts of marketing professionals to achieve competitiveness in the unpredictable business environment.

Big data analytics tools are the use of advanced analytic techniques targeting large and diverse volumes of data that include structured, semi-structured, and unstructured data from different sources and in different sizes from terabytes to zetabytes. The health sector is faced with the need to generate and manage large data sets from various health systems, such as electronic health records and clinical decision support systems. This data can be used by providers, clinicians, and policymakers to plan and implement interventions, detect disease more quickly, predict outcomes, and personalize care delivery. However, little attention is paid to the connection between big data analytics tools and the health sector. Thus, a systematic review of the bibliometric literature (LRSB) was developed to study how the adoption of big data analytics tools and infrastructures will revolutionize the healthcare industry. The review integrated 77 scientific and/or academic documents indexed in SCOPUS presenting up‐to‐date knowledge on current insights on how big data analytics technologies influence the healthcare sector and the different big data analytical tools used. The LRSB provides findings related to the impact of Big Data analytics on the health sector by introducing opportunities and technologies that provide practical solutions to various challenges.

Introduction: Alzheimer's disease (AD) is the first cause of dementia worldwide without any current curative treatment. Facing an increasing prevalence and its associated costs, AD represents a public health challenge. Usual diagnostic methods still rely on extended interviews and paper tests provided by an exterior examiner. We aim to create a novel, quick cognitive-screening tool on a numerical tablet. Methods: This program, built and edited with Unity®, runs on Android® for the Samsung Galaxy Tab S7 FE®. Composed of seven tasks inspired by the Mini-Mental Status Examination and the Montréal Cognitive Assessment, it browses several cognitive functions. The architectural design of this tablet application is distinguished by its multifaceted capabilities, encompassing not only seamless offline functionality but also a mechanism to ensure the singularity of data amalgamated from diverse sites. Additionally, a paramount emphasis is placed on safeguarding the confidentiality of patient information in the healthcare domain. Furthermore, the application empowers individual site managers to access and peruse specific datasets, enhancing their operational efficacy and decision-making processes. We performed a preliminary usability assessment among healthy subjects. Results: 24 healthy patients were included with a final F-SUS score of "excellent". Participants perceived the tool as simple to use and achieved the test in a mean time of 142 seconds. No technical errors occurred. Conclusion: These preliminary results suggest that our new assessment on a numerical tablet allows a short cognitive screening.

Cardiac myosin-binding protein C (MyBPC) is a thick-filament associated regulatory protein in the sarcomere. It regulates the sensitive contractile system of the myocardium by acting as a mechanical tether, sensitizing the thin filament or modulating myosin motor activity. Mutations in the MYBPC3 gene are a frequent cause for the development of hypertrophic cardiomyopathy, the most frequent cardiac disorder. Recently, the monoallelic double mutation MYBPC3Δ25bp/D389V has been discovered as a subset of the common MYBPC3Δ25bp variant in South Asia. MYBPC3Δ25bp/D389V carriers exhibit hyperdynamic features, which are considered an early finding for the development of hypertrophic cardiomyopathy. Using correlation-guided molecular dynamics simulations sampling, we show that the D389V mutation shifts the conformational distribution of the C2 domain of MyBPC. We further applied biochemical approaches to probe the effects of the D389V mutation on structure, thermostability and protein-protein interactions of MyBPC C2. The melting temperature (Tm) of MyBPC C2 D389V is decreased by 4 to 7 °C compared to wild type while the interaction of the C0-C2 domains with myosin and actin remains unchanged. Additionally, we utilized steered molecular dynamics (SMD) simulations to investigate the altered unfolding pathway of MyBPC C2 D389V. Based on our data, we propose a pathomechanism for the development of HCM in MYBPC3Δ25bp and MYBPC3Δ25bp/D389V carriers.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

Shale gas and coalbed methane are energy sources that partly or even mainly consist of methane stored in an adsorbed state in the pores of the organic-rich rock and coal seams. In this study, the graphene nanoslit model is employed to model the nanometer slit pores in shale and coal. The Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) modelling methods are used to investigate the mechanisms of adsorption and displacement of methane in the slit pore. It was found that the CVFF forcefield resulted in the largest adsorption amount, while the PCFF forcefield resulted in the least. The COMPASS and COMPASS II force fields led to similar results. As the width of the slit pore increases, the adsorption amount of gas molecules increases, and the number density profile of adsorbed methane molecules alters from a single adsorption layer to multi-adsorption layers. The minimum slit pore width at which methane molecules can penetrate the slit pore was found to be 0.7 nm. Moreover, it is demonstrated that by lowering the temperature, the adsorption rate of the methane increases since the adsorption is an exothermic process. Enhancing methane recovery was investigated by the injection of gases such as CO2 and N2 to displace the adsorbed methane. The comparison of adsorption isotherms of gas molecules provided the following order in terms of the amount of adsorption: CO2>CH4>N2.

In soil erosion estimation models, the variable with the greatest impact is rainfall erosivity (RE), which is the measurement of precipitation energy and its potential capacity to cause erosion, and erosivity density (ED), which relates RE to precipitation. The RE requires high temporal resolution records for its estimation. However, due to the limited observed information and the increasing availability of rainfall estimates based on remote sensing, recent research has shown the usefulness of using observed-corrected satellite data for RE estimation. This study evaluates the performance of a new gridded dataset of RE and ED in Peru (PISCO_reed) by merging data from the IMERG v06 product, through a new calibration approach with hourly records of automatic weather stations, during the period of 2000-2020. By using this method, a correlation of 0.7 was found between the PISCO\_reed and RE obtained by the observed data. An average annual RE for Peru of 4831 MJ·mm·ha-1·h-1 was estimated with a general increase towards the lowland Amazon regions and high values are found on the north-coast Pacific area of Peru. The spatial identification of the most risk areas of erosion, was carried out through a relationship between the ED and rainfall. Both erosivity data sets will allow us to expand our fundamental understanding and quantify soil erosion with greater precision.

Isotopic stable analysis (SIA) is a powerful tool in the assessment of different types of ecological and physiological studies. For that, different preservative methods for the samples are commonly used prior to isotopic analysis. The effects of various preservative methods (drying, freezing, ethanol and formaldehyde) have been analyzed for C:N ratio, δ13C and δ15N on a variety of tissues including dorsal fins (three seahorse and two pipefish species), seahorse newborns (three seahorses species), and prey (copepods and different stages of Artemia) commonly used to feed the fishes in rearing conditions. The aims of the study were to: (i) evaluate isotopic effects of preservation methods across tissues; and (ii) construct the first conversion models available in syngnathid fishes. The preservation in ethanol and to a lesser extend in formaldehyde significantly affected δ13C values, whereas δ15N signatures were not affected significantly. Due to their low lipid content, the isotopic signals in fish fins were almost unaffected, supporting the suitability of dorsal fins as a convenient tool in isotopic studies on vulnerable species such as syngnathids. The regression equations provided permit the successful conversion of δ13C and δ15N values between preservative treatments. The conversion models can be applied to isotopic studies in the field and in the laboratory.

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.

Background: The importance of knowing the workload of family nurses lies essentially in the possibility of improving health outcomes, care processes and the nurse’s professional life. There is a lack of studies that fully describe nursing workload in primary care, particularly, in the context of family health nursing, and the ideal metrics to be used remains unknown, making it impossible to characterize and therefor provide the necessary insight to acknowledge the different contributions of several aspects that embodies the global workload of family nurses. The objective of this scoping review was to map the known evidence and characterize the instruments used to assess the workload of family nurses. Methods: Scoping review, according the Joanna Briggs Institute proposed methodology for scoping reviews, consisting of 3 research stages: 1) initial research in Medline and CINHAL; 2) extended search, using keywords and search terms, in the following databases: JBI, CINAHL Complete, MEDLINE, Cochrane and Scopus; 3) Search the reference list of the selected articles. No time limit was defined. Results: Fourteen studies referring to ten as-sessment instruments were included. Nine of them analyze workload as a dimension of a broader instrument, and two studies refer to an instrument that focuses exclusively on workload. Con-clusions: The diversity of professional competencies and contexts, the conceptual complexity of workload and the absence of an theoretical framework, makes it difficult to identify consensual instruments to assess the workload of family nurses. This study was registered in Open Science Framework® with the following registration (https://osf.io/3k6vr).

Climate change, the scarcity of fossil fuels, technical advances in clean energy, and the volatility of crude oil prices are just a few of the factors that have prompted the world to recognize clean energy as a viable alternative to dirty energy. As part of the Paris Climate Accord of 2015, many countries agreed to change their economies to be more sensitive to climate change. Due to this Accord, which increased interest from investors and decision-makers, investments in clean energy companies have benefited [1,2]. Clean energy stocks, which are a part of the larger world of tradable reserves, might experience pricing inefficiencies. In this paper, we investigate the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets like gold, crude oil, and natural gas between January 1, 2018, and March 9, 2023, which covers periods of low volatility and financial instability (2020 and 2022 events). To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings demonstrated that both periods exhibit severe multifractal and significant asymmetry, indicating that the price indices under study are not at all efficient.

This study investigates the relationship between clean and dirty energy markets, specifically focusing on clean energy stock indexes and their potential as hedging assets and safe havens during periods of global economic uncertainty. The research analyzes five clean energy indexes and five dirty energy indexes from May 2018 to May 2023, considering events like the global pandemic and the Russian invasion of Ukraine. The main objective is to examine the causal relationship among different stock indexes pertaining to dirty and clean energy by using the Granger causality test (VAR Granger Causality/Block Exogeneity Wald Test) to determine whether clean energy indexes can predict future prices of dirty energy indexes. However, the findings reveal that clean and dirty energy indexes do not exhibit hedging characteristics or serve as safe havens during times of economic uncertainty, rejecting the research question. These results have important implications for investment strategies, as assets lacking safe haven characteristics may not preserve portfolio efficiency in uncertain times. The study's insights provide valuable guidance for investors, poli-cymakers, and participants in energy financial markets. It highlights the need to adapt investment approaches and seek alternative options to navigate uncertain economic conditions effectively.

The most common method for establishing bioequivalence (BE) is to demonstrate similarity of concentration-time profiles in the systemic circulation, as a surrogate to the site of action. However, the similarity, or otherwise, of profiles from two different formulation in the gastrointestinal tract (GIT) may not be associated with same conclusions based on systemic circulation. Here, we have explored the concordance of BE conclusions (or otherwise) for a set of hypothetical formulations based on drug concentration-profiles in various segments of gut vs those in systemic circulation using virtual trials powered by physiologically-based (PBPK) models. Moreover, by changing physiological and biological attributes of the GIT, the impact of Crohn’s Disease on the BE conclusions was explored. The virtual BE (VBE) was applied to an Entocort EC, a pH/time-dependent release formulation of budesonide, as model drug that is targeted at ileum and colon. Substantial “discordance” between the local and systemic outcomes of VBE was observed. Upper GIT segments were much more sensitive to formulation changes than systemic circulation, where the latter led to false conclusions for BE. The ileum and colon showed a lower frequency of discordance with systemic-derived VBE. Nonetheless, a higher f2 value than the default similarity standard (50) was required to achieve local BE. In the case of Crohn’s Disease, a product-specific f2 value might be needed for drugs such as Entocort EC to ensure local BE, knowing the insensitivity of systemic data to show lack of BE. The results, being limited to the single model drug product, Entocort EC, may not provide a a general and conclusive picture. However, for the first time, it demonstrated the potential discordances between the local gut vs systemic BE.

The valorization of the large amount of crude glycerol formed from biodiesel industry, is of primordial necessity. One possible direction with high interest to the biorefiniery sector is the production of fuel additives as solketal, though the acetalization of glycerol with acetone. This is a chemical process that conciliates high sustainability and economic interest, since solketal contributes to the fullfilment of a Circular Economy Model through its use in biodiesel blends. The key to guarantee high efficiency and high sustainability for solketal production is the use of a recovery and recyclable heterogeneous catalyst. Some examples are already reported in the literature (first example in 2012), and this review intends to conciliate the information spreaded in this topic and established the most important reacional parameters and the main catalytic characteristics strategies to achieve high solketal production in short reaction time.

One of the most broadly used models for membrane fouling is the Hermia model, which separates this phenomenon into four blocking mechanisms, each with an associated parameter n. These mechanisms are complete blocking (n=2), intermediate blocking (n=1), standard blocking (n=3/2), and cake formation (n=3/2). The original model, which was obtained through experimental data, is given by an Ordinary Differential Equation (ODE) dependent on n. At the time, this ODE was only solved for these four values of n, which limits the effectiveness of the model when adjusted to experimental data. This paper aims to not only mathematically prove the original Hermia model but also to broaden the scope of this model for any real number n by using the original ODE, the equations of fluid mechanics, and the properties of single and multivariable calculus. The extended Hermia model (EHM) is given by a power law for any n≠2 and is given by an exponential function at n=2. To better test the model, we have performed the model fitting of the EHM and compared its performance to the original four pore-blocking mechanisms in 6 micro- and ultrafiltration examples. In all examples, the EHM performed consistently better than the four original pore-blocking mechanisms. Changes in the blocking mechanisms concerning transmembrane pressure (TMP), crossflow rate (CFR), crossflow velocity (CFV), membrane composition, and pretreatments are also discussed.

This study involved a comprehensive examination of sensory attributes in Bísaro dry-cured loins, including odor, androsterone, scatol, color, fat color, hardness, juiciness, chewiness, flavor intensity, and flavor persistence. Analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveil distinct peaks associated with significant components such as protein, lipid, and water. Support Vector Regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization, and radial base kernel (non-linear SVR model). The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616 - 0.9955) and low RMSE values (0.0400 – 0.1031). The prediction set's relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig aroma, hardness, fat color, and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment.

The separator membrane is an essential component of lithium-ion batteries, separating the anode and cathode and controlling the number and mobility of the lithium ions. Among the polymer matrices most investigated for battery separators are poly(vinylidene fluoride) (PVDF) and its copolymers poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE), poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), and poly(vinylidene fluoride-cochlorotrifluoroethylene) (PVDF-CTFE), due to their excellent properties such as high polarity and the possibility of controlling the porosity of the materials through binary and ternary polymer/solvent systems, among others. This review presents the recent advances on battery separators based on poly(vinylidene fluoride) (PVDF) and its copolymers for lithium-ion batteries. It is divided in the following sections: single polymer and co-polymers, surface modification, composites and polymer blends. Further, a critical comparison between those membranes and other separator membranes is presented, as well as the future trends on this area.

This study aimed to analyze the effect of a flow training program based on mindfulness applied to young and adult elite handball athletes. A quantitative, quasi-experimental, descriptive data analysis approach was carried out. The sample included 105 athletes (51 female and 54 male). The athletes were divided into two groups: i) experimental (n = 53) and ii) control (n = 52). The results of the repeated ANOVA indicated that the experimental group achieved significant improvements compared to the control group in decision making (n2p=.086), mental well-being (n2p=.045), dispositional flow state (n2p=.103), non-judgment (n2p=.040), refocusing (n2p=.052) and mindful trait in daily life (n2p=.058). In the linear regression test, the factor non-judgment was identified as a predictor of decision making (F(103)=7.99, p=.006) and the predictor for the mental well-being were dispositional flow state (F(102)=29.2, p

Herein, we present a combination of experimental and computational study on the mitochondrial F0F1-ATPase nanotoxicity inhibition induced by single-walled carbon nanotubes (SWCNT-pristine, SWCNT-COOH). To this end, the in vitro inhibition responses in submitochondrial particles (SMP) as F0F1-ATPase enzyme were strongly dependent on the concentration assay (from 3 to 5 µg/ml) for both types of carbon nanotubes. Besides, both SWCNTs show an interaction inhibition pattern like the oligomycin A (the specific mitochondria F0F1-ATPase inhibitor). Furthermore, the best crystallography binding pose obtained for the docking complexes based on the free energy of binding (FEB), fit well with the previous in vitro evidences from the thermodynamics point of view. Following an affinity order as: FEB (oligomycin A/F0-ATPase complex) = -9.8 kcal/mol > FEB (SWCNT-COOH/F0-ATPase complex) = - 6.8 kcal/mol ~ FEB (SWCNT-pristine complex) = -5.9 kcal/mol. With predominance of van der Waals hydrophobic nanointeractions with key F0-ATPase binding site residues (Phe 55 and Phe 64). By the other hand, results on elastic network models, and fractal-surface analysis suggest that SWCNTs induce significant perturbations by triggering abnormal allosteric responses and signals propagation in the inter-residue network which could affect the substrate recognition ligand geometrical specificity of the F0F1-ATPase enzyme in order (SWCNT-pristine > SWCNT-COOH). Besides, the performed Nano-QSTR models for both SWCNTs show that this method may be used for the prediction of the nanotoxicity induced by SWCNT. Overall, the obtained results may open new avenues toward to the better understanding and prediction of new nanotoxicity mechanisms, rational drug-design based nanotechnology, and potential biomedical application in precision nanomedicine.

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

This study analyzes the eating behavior and factors associated with the presence of disordered eating attitudes in patients undergoing bariatric surgery. It is a cross-sectional, descriptive, and analytical study conducted at a hospital in the Amazon region of Brazil. The Disordered Eating Attitude Scale reduced version (DEAS-s) was used to assess the risk of eating disorders and the Three-Factor Eating Questionnaire (TFEQ-R21) to characterize eating behavior. A total of 205 patients participated, with a mean age of 37.5 ± 8.6 years, the majority being female (93.7%; p<0.001), the mean BMI was 45.3±6.7 kg/m2. It was found that cognitive restraint had the highest mean (52.6±19.9; p<0.001). As for the DEAS-s, the question with the highest mean was "spending one or more days without eating or consuming only liquids to lose weight" (2.80±1.99). Female participants had a higher score in the emotional eating (p=0.016). Disordered eating attitudes showed a correlation with emotional eating and uncontrolled eating. These results suggest that candidates for bariatric surgery may have susceptibility to eating disorders. The importance of a multidisciplinary team in monitoring during the preoperative period is highlighted.

(1) Background: The purpose of this study was to investigate the relationship between IMO and burnout while assessing the contribution of job demands and resources on increasing internal orientation and worker well-being and, consequently, the levels of perceived performance; (2) Methods: Data were collected between April and December 2021 by completing an online questionnaire, developed in the Google Forms platform. The following descriptive statistics were analyzed: measures of central tendency (mean), dispersion (standard deviation), minimum value and maximum value. Next, Pearson's correlation coefficient was calculated to analyze the relationship between the variables under study.; (3) Results: The results showed the mediating effect of IMO between performance feedback and perceived performance, while burnout mediates the relationship between emotional and technology demands and perceived performance. (4) Conclusions: These conclusions demonstrate that constructive feedback might help a more efficient performance through better internal communication and the positive effects of technology demands could be the result of the interaction between personal and organizational resources.

Considering the various problems caused by infiltration in civil construction, this study aimed to identify the most appropriate waterproofing methods for different types of surfaces. A study was conducted on the mechanisms of water infiltration on surfaces and the waterproofing methods available on the market, focusing on asphalt blankets, in addition to a literature review highlighting state-of-the-art on this topic. A case study was also conducted in residence in Nova Lima, Brazil, analyzing different waterproofing techniques, including their characteristics and stages. Among the conclusions, it is highlighted that the implementation of adequate project, installation, inspection, and maintenance techniques can significantly reduce the waterproofing failure rate and repair costs and that the excellent choice of materials, along with the skill of the labor force in the application, is fundamental to guarantee the adequate performance of these materials in buildings.

The watershed hydrologic conditions in the Madre de Dios (MDD) basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land use cover. These changes have also had detrimental effects on the geomorphology, water quality, and aquatic habitat within the basin. However, there is a scarcity of hydrological modeling studies in this area primarily due to the limited availability of hydrometeorological data. The primary objective of this study was to examine how deforestation impacts the hydrological conditions in the MDD basin. By implementing the Soil and Water Assessment Tool (SWAT) model, this study determined that replacing 12% of the evergreen broadleaf forest area with bare land resulted in an significant increase in surface runoff by 38% monthly, a reduction of evapotranspiration by 1% annually, and an average monthly streamflow increase of 12%. Changes in spatial patterns reveal that the primary impacted watershed is the Inambari River subbasin, a significant tributary of the Madre de Dios River. This area experiences an annual average surge of 187% in surface runoff generation while witnessing an annual average reduction of 8% in evapotranspiration.These findings have important implications, as they can contribute to instances of flooding and extreme inundation events, which have already occurred in the MDD region.

The objective of this work was the use of goat and sheep liquid whey concentrates (LWCs) produced by ultrafiltration (UF) for the manufacture of frozen yoghurts with or without different concentrations of inulin. In a first step, natural yoghurts using only goat and sheep LWCs as raw material were obtained. One day after production, these yoghurts were used to produce frozen yoghurts with different concentrations of added inulin. The physicochemical charateristics of ewe´s and goat´s yoghurts were significantly different regarding dry matter, protein, fat and minerals. Ewe´s yoghurts were solids while goat´s yoghurts behaved as a viscous liquid. Frozen yoghurts with different levels of inulin addition also presented significant differences concerning physicochemical and microbiological characteristics. Overrun was similar for all formulations except for the one produced with ewe’s LWC containing 5.0% inulin, which presented a significantly higher value. Higher meltdown rates in goat’s whey frozen yoghurts were observed. The survival rates of lactic acid bacteria were lower than data reported for similar products. Concerning sensory acceptance, both products showed encouraging results. It can be considered that the production of frozen yoghurts by using LWCs as main ingredient can be an interesting option to broaden the product’s portfolio of small/medium scale dairy producers.

Hydrogen gas is seeping from the sedimentary basin of São Franciso, Brazil. The seepages of H₂ are accompanied by helium whose isotopes reveal a strong crustal signature. Geophysical data indicates that this intra-cratonic basin is characterized by i) a relatively high geothermal gradient, ii) deep faults delineating a horst and graben structure and affecting the entire sedimentary sequence, iii) an archean to paleoproterozoïc basements enriched in radiogenic elements and displaying mafic and ultramafic units, and iv) a possible karstic reservoir located 400 m below the surface. The high geothermal gradient could be due to a thin lithosphere enriched in radiogenic elements, which can also contribute to a massive radiolysis process of water at depth, releasing an important amount of H₂. Alternatively, ultramafic rocks that may have generated H₂ during their serpentinization are also documented in the basement. The seismic profiles show that the faults seen at the surface are deeply rooted in the basement, and can drain deep fluids to shallow depths in a short time scale. The carbonate reservoirs within the Bambuí group which forms the main part of the sedimentary layers are crossed by the fault system and represent good candidates for temporary H₂ accumulation zones. The formation by chemical dissolution of sinkholes located at 400 m depth might explain the presence of sub-circular depressions seen at the surface. These sinkholes might control the migration of gas from temporary storage reservoirs in the upper layer of the Bambuí formation to the surface. The very high fluxes of H₂ escaping out of these structures which have been recently documented are, however, in disagreement with the newly developed H₂ production model in the Precambrian continental crust. They either question the validity of these models or the measurement methodology.

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.

The Republic of Djibouti is a small country in the Horn of Africa and, as in most developing countries, rain gauges are sparse and data are scarce. This study aims to report on the reliability of gridded precipitation datasets (P datasets) across the Republic of Djibouti through direct comparisons with rain gauge measurements from the annual to the daily time scales. Our specific objective is to be able to use such products in the context of hydrological modeling at a daily time step. Given the scarcity of available data in the Republic of Djibouti, our study was carried out on two time windows (1980-1990 and 2008-2013) and two gauge networks with different spatial resolutions: the southeast of the Republic of Djibouti (5000 km2) and the Ambouli catchment (794 km2), which drains the city of Djibouti. The reliability of these products is analyzed with quantitative metrics and categorical metrics, exclusively at a daily time step for the latter. The performance of the P datasets degrades from the annual time scale to the daily time scale. Even though the same products exhibit the best performance at the various time scales, the performance of most of the products differs from one spatial scale to another. Our results demonstrate the importance of the temporal and spatial windows, as the same products can perform differently according to the scale. For all the spatiotemporal scales, the most reliable product is MSWEP v.2.2. This P dataset is derived from a combination of satellite products (multiple sensors such as infrared and passive microwave), reanalysis products, and rain gauge observations. A strong discrepancy between rain gauge observations and P datasets is revealed according to the categorical metric at a daily time step. The analysis of rainfall events triggering runoff, using a 10 mm rainfall threshold showed that the most efficient products were unable to accurately detect such events at a daily time step, with a significant underestimation of rainfall events higher than 10 mm. None of these products, even the most reliable, can be used for a calibration/validation of a hydrological model at a daily time step.

Green investors have expressed concerns about the environment and sustainability due to the high energy consumption involved in cryptocurrency mining and transactions. This article investigates the safe haven characteristics of clean energy stock indexes in relation to 3 cryptocurrencies, taking into account their respective levels of "dirty" energy consumption from May 16, 2018, to May 15, 2023. By virtue of analyzing a tumultuous era in the global economy, the level of integration between clean energy stock indexes and cryptocurrencies will be inferred by using Gregory and Hansen's methodology. Furthermore, to assess the presence of a volatility spillover effect between clean energy stock indexes and “dirty-classified” cryptocurrencies, the ?-test of heteroscedasticity of two samples from Forbes and Rigobon will be employed. The empirical findings show that clean energy stock indexes may offer a viable safe haven for dirty energy cryptocurrencies. However, the precise associations differ depending on the cryptocurrency under examination. The implications of the study's results are significant for investment strategies, this knowledge can inform decision-making procedures and facilitate the adoption of sustainable investment practices. Investors and policymakers can gain a deeper understanding of the interplay between investments in renewable energy and the cryptocurrency market.

Ostreococcus tauri is a simple unicellular green alga representing an ecologically important group of phytoplankton in oceans worldwide. Modern molecular techniques must be developed in order to understand the mechanisms that permit adaptation of microalgae to their environment. We present for the first time in O. tauri a detailed characterization of individual genomic integration events of foreign DNA of plasmid origin after PEG-mediated transformation. Vector integration appears to be random, occurring mainly at a single locus, and thus confirming the utility of this technique for insertional mutagenesis. While the mechanism of double-stranded DNA repair in the O. tauri model remains to be elucidated, we clearly demonstrate by genome resequencing that the integration of the vector leads to frequent structural variations (deletions/insertions and duplications) and some chromosomal rearrangements in the genome at the insertion loci, and often within the vector sequence itself. From these observations, we speculate that a non-homologous end joining-like mechanism is required during random insertion events, as described in plants and other freshwater algal models. PEG-mediated transformation is therefore a promising molecular biology tool, not only for functional genomic studies, but also for biotechnological research in ecologically important marine algae.

The growing interest in Na-ion batteries as a “beyond lithium” technologies for energy storage drives the research for high-performance and environment-friendly materials. Na2Ti3O7 (NTO) as an eco-friendly, low-cost anode material shows a very low working potential of 0.3 V vs Na+/Na but suffers from poor cycling stability, which properties can be significantly influenced by materials synthesis and treatment. Thus, in this work, the influence of the calcination time on the electrochemical performance and the reaction mechanism during cycling were investigated. NTO heat-treated for 48 h at 800 °C (NTO-48h) demonstrated enhanced cycling performance in comparison to NTO heat-treated for only 8 h (NTO-8h). The pristine material was thoroughully characterized by X-ray diffraction, laser granulometry, X-ray photoelectron spectroscopy, and specific surface area measurements. The reaction mechanisms induced by sodiation/desodiation and cycling were investigated by opernado XRD. Electrochemical impedance spectroscopy was used to evidence the evolution of the solid electrolyte interface layer (SEI) and modification of charge transfer resistances as well as the influence of cycling on capacity decay. The evolution of the crystallographic structure of NTO-48h revealed a more ordered structure and lower surface contamination compared to NTO-8h. Moreover, the residual Na4Ti3O7 phase detected after the sodium extraction step in NTO-8h seems correlated to the lower electrochemical performance of NTO-8h compared to NTO-48h.

A novel polymer containing β-cyclodextrin, α-cyclodextrin, γ -cyclodextrin and chitosan (cy-clodextrin-chitosan) was synthesized, characterized and used for extracting two kinds of pharmaceuticals ibuprofen and progesterone. This polymer is amorphous and porous with a high swelling capacity. The cyclodextrin-chitosan polymer exhibits high extraction capacity towards progesterone and ibuprofen. Add to that, the effect of different operator variables was studied and discussed (i.e., the effects of contact time, solute concentration, pH, ionic strength and temperature). In this study adsorption kinetic was investigated, where it follows a pseudo-second order model in case of ibuprofen and progesterone.

Background: Protein CCDC186 is involved in the maturation of dense core vesicles in the trans-Golgi network in neurons and endocrine cells. To date, only one patient, within a large sequencing study of 1000 cases, and a single case report with variants in CCDC186 had previously been described. However, no functional studies in any of these two cases had been performed. Methods: Exome sequencing from one affected individual of each family was performed. In addition, Sanger sequencing of the parents and one of the affected siblings was also performed. CCDC186 protein was assessed in cultured fibroblasts or muscle tissue by western blot. Transcriptomic analysis was done by means of RNA sequencing. Results. We identified three patients from two gypsy families, unrelated to each other, with the same homozygous mutations in CCDC186 gene. Clinically, all patients presented with seizures, frontotemporal atrophy, hypomyelination, recurrent infections, and endocrine disturbances such as severe non ketotic hypoglycemia. Low levels of cortisol, insulin or growth hormone could only be verified in one patient. All of them had a neonatal onset and died between 7 months and 4 years of age. WES identified a homozygous variant in CCDC186 gene (c.2215C>T, p.Arg739Ter) in the index patients of both families. Protein expression studies demonstrated that the CCDC186 was practically undetectable in fibroblasts and muscle tissue. These observations correlated perfectly with the transcriptomic analysis performed in fibroblasts in one of the patients, which showed a significant reduction of CCDC186 mRNA levels. Conclusion. Our study provides functional evidence that mutations in this gene have a pathogenic effect on the protein and reinforces CCDC186 as a new disease-associated gene. In addition, mutations in CCDC186 could explain the combined endocrine and neurologic alterations detected in our patients

The search for new food products that promote consumers health has always been of great interest. The dairy industry is perhaps the best example regarding the emergence of new products with claimed health benefits. Cheese whey (CW), the by-product resulting from cheese production, and second cheese whey (SCW), which is the by-product of whey cheese manufacture, have proven to be potential ingredients for the development of food products with improved nutritional characteristics and other functionalities. Nowadays, due to their nutritional quality, whey products have gained a prominent position among healthy food products. However, for long, CW and SCW were usually treated as waste or as animal feed. Due to their high organic content, these by-products can cause serious environmental problems if discarded without appropriate treatment. Small and medium size dairy companies do not have equipment and structure to process whey and second cheese whey. In these cases, generally, they are used for animal feed or discarded without an appropriate treatment, being the cause of several constraints. There are several studies regarding CW valorization and there is a wide range of whey products in the market. However, in the case of SCW remains a lack of studies regarding its nutritional and functional properties, as well as ways to reuse this by-product in order to create economic value and reduce environmental impacts associated to its disposal.

Diarylethene is a prototypical molecular switch that can be reversibly photoisomerized between its open and closed forms. Ligands bpy-DAE-bpy, consisting of a phenyl-diarylethene-phenyl (DAE) central core and bipyridine (bpy) terminal substituents, are able to self-organize. They are investigated by scanning tunneling microscopy at the solid-liquid interface. Upon light irradiation, cooperative photochromic switching of the ligands is recognized down to the sub-molecular level. The closed isomers show different electron density of states (DOS) contrasts, attributed to the HOMO or LUMO molecular orbitals observed. More importantly, the LUMO images show remarkable differences between the open and closed isomers, attributed to combined topographic and electronic contrasts mainly on the DAE moieties. The electronic contrasts from multiple HOMO or LUMO distributions, combined with topographic distortion of the open or closed DAE, are interpreted by density functional theory (DFT) calculations.

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.

Titanium dioxide (TiO2) and aluminum oxide (Al2O3) coatings have been investigated in a wide range of bio-applications due to their biodegradation and biocompatibility properties, that are key parameters for their use in the food packaging and biomedical devices fields. The present study evaluates and compares the electrochemical behavior of the non-coated, commercial resin-coated, TiO2-coated and Al2O3-coated aluminum in commercial beer electrolyte. For this, TiO2 and Al2O3 thin films were deposited on aluminum (Al) substrates using atomic layer deposition (ALD). The evaluation of the corrosion barrier layer properties was performed by linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). In addition, profilometry, grazing incidence X-ray diffractometry (GIXRD), scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FT-IR) analyses were performed to investigate the physical and chemical properties of the pristine and / or corroded samples. TiO2 and Al2O3 films presented an amorphous structure, a morphology that follows Al substrate surface, and a thickness of around 100 nm. Analysis of LSV data showed that ALD coatings promoted a considerable increase in corrosion barrier efficiency being 86.3% for TiO2-coated Al and 80% for Al2O3-coated Al in comparison with 7.1% of commercial resin-coated Al. This is mainly due to the lower electrochemical porosity, 11.4% for TiO2-coated Al and 20.4% for Al2O3-coated Al in comparison with 96% of the resin-coated Al, i.e. an increase of up to twofold in the protection of Al when coated with TiO2 compared to Al2O3 coated. The EIS results allow us to complement the discussions about the reduced corrosion barrier efficiency of the Al2O3 film for beer electrolyte once SEM and FT-IR analyzes did not show drastic changes in both investigated ALD films after the corrosion assays. The above results indicate that ALD TiO2 and Al2O3 films may be a viable alternative to replace the synthetic resin coatings frequently used in aluminum cans of use in the food industry.

Stress is an inherent sensation of being unable to handle demands and occurrences. If not properly managed, stress can develop into a chronic condition, leading to the onset of additional chronic health issues like cardiovascular illnesses and diabetes. Various stress meters have been suggested in the past, along with diverse approaches for its estimate. However, in the case of more serious health issues such as hypertension and diabetes, the results can be significantly improved. This study presents the design and implementation of a distributed wearable sensor computing platform with multiple channels. The platform aims to estimate stress levels in diabetes patients by utilizing a fuzzy logic algorithm that is based on the assessment of several physiological indicators. Additionally, a mobile application was created to monitor users' stress levels and integrate data on their blood pressure and blood glucose levels. Validation experiments were performed on patients with chronic diabetes, and the initial findings are presented in the study.

Chondroitin is a glycosaminoglycan that has gained widespread use in nutraceuticals and pharmaceuticals, mainly for treating osteoarthritis. Traditionally, it has been extracted from animal cartilage but recently, biotechnological processes have emerged as a commercial alternative to avoid the risk of viral or prion contamination and offer a vegan-friendly source. Typically, these methods involve producing the chondroitin backbone using pathogenic bacteria and then modifying it enzymatically through the action of sulfotransferases. Despite the challenges of expressing active sulfotransferases in bacteria, the use of eukaryotic microorganisms is still limited to a few works using Pichia pastoris. To create a safer and efficient biotechnological platform, we have constructed a biosynthetic pathway for chondroitin production in S. cerevisiae as a proof-of-concept. Up to 125 mg/L and 200 mg/L of intracellular and extracellular chondroitin were produced, respectively. Furthermore, as genome-scale models are valuable tools for identifying novel targets for metabolic engineering, a stoichiometric model of chondroitin-producing S. cerevisiae has been developed and used in optimization algorithms. Our research has yielded several novel targets, such as uridine diphosphate(UDP)-N-acetylglucosamine pyrophosphorylase (QRI1), glucosamine-6-phosphate acetyltransferase (GNA1) or N-acetylglucosamine-phosphate mutase (PCM1) overexpression that might enhance chondroitin production, which will guide future experimental research to develop more efficient host organisms for the biotechnological production process.

Dietary protein quality plays a key role in maintaining intestinal mucosal integrity, but also modulates the growth of luminal microorganisms. This work assessed the effect of dietary protein sources on the performance, gut morphology, and microbiome in Nile tilapia. Four isonitrogenous and isolipidic diets comprising equivalent amounts of the protein supply derived from either PLANT, ANIMAL, INSECT, or MICROBIAL (bacterial biomass) sources were fed to triplicate groups of fish (IBW: 12 g) during 46 days. Fish fed ANIMAL and MICROBIAL diets showed significantly higher growth than those fed the PLANT and INSECT diets (P < 0.05). Relative abundance at the phylum level shows Bacteroidetes, Fusobacteria and Proteobacteria as more abundant phyla in tilapia’s intestine, while Cetobacterium is the most representative genera in all treatments. Interesting patterns were observed in the correlation between amino acid intake and genus and species abundance. Metabolism prediction analysis showed that microbial amine and polyamine degradation pathways are modulated depending on diets. In conclusion, different protein sources interfere directly with the cross-talk of bacteria pathways and amino acid intake.

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.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at &lt; .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p &lt; .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p &lt; .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

Hard tissue apposition along the root canal walls is a slow, normally occurring physiological aging process. In response to tooth wear, local deposition of hard tissue may also occur in the pulp at a slow pace. Sometimes, the rate of hard tissue deposition acceleration may seem to be uncontrolled after dental trauma, autotransplantation, and orthodontic therapy, leading to rapid partial or total obliteration of the root canal space. This situation is called calcific metamorphosis (CM) or pulp canal obliteration (PCO). Although the incidence of pulpal necrosis in these teeth is believed to be infrequent, conventional endodontic therapy in severely calcified canals poses extreme difficulties and a higher risk for procedural accidents. This article aims to review the available approaches for the predictable negotiation of calcified canals and to introduce the buckling resistance activation test (BRAT) technique.

This study investigates the relationship between energy metals and precious metals to assess their suitability as safe haven assets in clean energy investment portfolios. It focuses on the impact of events in 2020 and 2022, characterized by substantial investments in clean energy. The research reveals that, except for Nickel Futures (NICKELc1), energy metals are positively linked with clean energy indexes. This suggests that they can serve as a secure investment option for green investors looking to diversify their portfolios. As a result, the study dismisses the initial question, indicating that energy metals can indeed be considered safe havens within the context of clean energy investments. Additionally, the research reinforces prior findings that precious metals like gold, silver, and platinum possess safe haven characteristics in relation to specific clean energy stock indexes. These results have significant implications, particularly given the increasing investments in clean energy stocks and the recurring uncertainties in the market. In summary, this study supports the idea that both energy metals and precious metals can play valuable roles in clean energy portfolios, providing stability during turbulent times in the market.

Accurate channel estimation is of utmost importance for massive MIMO systems to provide significant improvements in spectral and energy efficiency. In this work, we present a study on the distribution of a simple but yet effective and practical channel estimator for multi-cell massive MIMO systems suffering from pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without previous knowledge of the inter-cell large-scale channel coefficients and noise power, asymptotically approximating the performance of the linear MMSE estimator as the number of antennas increases. We prove that the distribution of the proposed channel estimator can be accurately approximated by the circularly-symmetric complex normal distribution, when the number of antennas, M, deployed at the base station is greater than 10.

Conclusions: It could be concluded that small/medium scale dairy plants can use UF equipment with the aim to valorize sheep´s and goat´s CW through the production of dairy formulations with added prebiotics and probiotics, while reducing the environmental impact of their activities.

In this paper, we identify issues and possible solutions in the key area of large-scale antenna systems, also know as Massive Multiple Input Multiple Output (MIMO) systems. Additionally, we propose the use of Massive MIMO technology as a means to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), the capacity of the MTC network and, in turn, that of the whole system, can be increased by grouping Machine-Type Communication (MTC) devices into clusters and letting each cluster share the same time-frequency physical resource blocks. We study the feasibility of applying sub-optimal linear detection to the problem of detecting a large number of MTC devices sharing the same time-frequency resources at the uplink of a base station (BS) equipped with a large number of antennas, M. In our study, we derive the achievable lower-bound rates for the studied sub-optimal linear detectors and show that the transmitted power of each MTC device can be reduced as M increases, which is a very important result for powerconstrained MTC devices running on batteries. Our simulation results suggest that, as M is made progressively larger, the performance of sub-optimal linear detection methods approach the matched filter bound, also known as perfect interference-cancellation bound.

Malassezia species are part of human commensal microbiota and is also related to diseases. Little is known about the interaction of these microorganisms with their host. Here we established two standard culture conditions for Malassezia spp. to perform infection assays using C. elegans and T. molitor. Invertebrate hosts infected by Malassezia spp. cultured in M9M resulted in higher death rate on survival assays when compared to yeasts cultured in standard Dixon medium indicating that M9M cultured Malassezia species have increased virulence. The culture and infection conditions established in this work, using invertebrate alternative models, are valuable tools to understand Malassezia-host interaction.

Glycerol is the main residue in the biodiesel production industry; therefore, their valorisation is crucial. Acetalization of glycerol towards fuel additives as solketal (2,2-dimethyl-1,3-dioxolan-4-methanol) is of high interest, promoting circular economy since it can be added to the biodiesel or even fossil-diesel to improve their quality and efficiency. Straightforward prepared metal-organic framework (MOF) materials of MOF-808 family were applied to the valorisation of glycerol for the first time. In particular, MOF-808(Hf) revealed to be an effective heterogeneous catalyst to produce solketal under moderate conditions: small amount of the MOF material (only 4wt% of glycerol), ratio 1:6 of glycerol/acetone and temperature of 60 ºC. The high efficiency of MOF-808(Hf) was associated with the high amount of acid centres present in its structure. Furthermore, its structural characteristics such as window opening cavities size and pore diameters showed to be ideal to reuse this material during at least ten consecutive reaction cycles without losing activity (conversion &gt; 90% and selectivity &gt; 98%). Remarkably, it was not necessary the washing or other activation treatment of the MOF-808(Hf) catalyst between cycles (no pore blockage occurred) and it maintained structural integrity after the ten cycles, confirming to be a sustainable heterogeneous catalyst to the glycerol valorisation.

IHepatitis C virus (HCV) has a high genetic diversity, with seven genotypes with 86 subtypes. This genetic variability confers persistence in the infection and escape of the immune system with evolution to cirrhosis and cancer. Environmental factors can contribute to different disease progression, being essential to assess the viral genotype in the infection and discuss the environmental particularities of Eastern Amazon, and the frequencies of Liver fibrosis between different HCV genotypes in patients living in a region of the Brazilian Eastern Brazilian Amazon. Consists in an observational cross-sectional study. Sociodemographic and clinical data of 76 individuals diagnosed with Hepatitis C between 2019 and 2020 in public health services were selected. Data collected was tabulated in Microsoft Excel 2010TM spreadsheets and analysed in GraphPad Prism 5.0TM. Liver fibrosis was associated with genetic subtypes. Subtype 1b was predominant (42.1%), followed by 1a (13%) and 3a (1.3%). 69.7% of participants had chronic hepatitis, with mild fibrosis (F1/F2) being the most prevalent (38.1%). Severe fibrosis was detected in 75% of individuals infected with the subtype 1b, that is associated with more severe disease. We suggest further studies, to assess other communities in the region, as well as the monitoring of these patients with Liver Elastography to determine the disease evolution and its better management.

The aim of the present study was to investigate the acute effect of caffeine supplementation on performance in official soccer matches. In double-blind, randomized crossover design, 13 professional soccer players performed two complete matches, with Caffeine (CAF) (6 mg/kg) and placebo (PLA) supplementation. Two-way repeated measures ANOVA showed that there was no effect of supplementation on the total distance covered (p = 0.536; ŋp² =0.033) or the total distance covered at different speeds (p = 0.453; ŋp² = 0.048), acceleration or deceleration (p = 0.387; ŋp² = 0.063) number of sprints (p = 0.521; µ² = 0.035) Heart Rate mean (p = 0.484; ŋp² = 0.042) Heart Rate maximum (p = 0.110; ŋp² = 0.199), Rate Perceived Effort (p = 0.151) or efficiency index (p = 0.480). Therefore, acute caffeine supplementation not effective to increase the performance of soccer players in official matches.

In Brazil, malaria transmission is mostly confined to the Amazon, where substantial progress has been achieved towards disease control in the past decade. Vector control has been historically considered a fundamental part of the main malaria control programs implemented in Brazil. However, the conventional vector-control tools have been insufficient to eliminate local vector populations due to the complexity of the Amazonian rainforest environment and ecological features of malaria vector species in the Amazon, especially Anopheles darlingi. Malaria elimination in Brazil and worldwide eradication will require a combination of conventional and new approaches that takes into account the regional specificities of vector populations and malaria transmission dynamics. Here we present an overview on both conventional and novel promising vector-focused tools to curb malaria transmission in the Brazilian Amazon. If well designed and employed, these new vector-based approaches may improve the implementation of malaria-control programs, particularly in remote or difficult-to-access areas and in regions where existing interventions have been unable to eliminate disease transmission. However, much effort still has to be put on research expanding the knowledge of neotropical malaria vectors to set the steppingstones for the development of such innovative tools.

Background: Porteirinha is endemic for visceral leishmaniasis (VL), with intense disease transmission of the disease. We evaluated the impact of canine euthanasia as a single control measure on the incidence of VL in humans and canines. Methods: A prospective observational cohort study was carried out over four years (1998–2002) in eight of the 12 neighborhoods of the city. The dynamics of canine visceral leishmaniasis (CVL) transmission were evaluated for 2 years, before beginning the screening-culling intervention. The comparative morbidity index (CMI) was used to stratify areas with the greatest risk of CVL, and the spatial distribution of human and canine VL cases was compared using univariate and bivariate K functions. Results: Human cases conglomerated in three neighborhoods. Spatial clusters were detected for CVL in 1998, 2000, and 2001, but not in 1999, when greater spatial dispersion occurred. The screening and culling intervention reduced the number of human VL cases and decreased the incidence of CVL, mainly in neighbor-hoods with a high CMI. Conclusions: The systematic euthanasia of seropositive dogs was shown to be an effective control action of the Program for Control of Visceral Leishmaniasis (PCLV) in Brazil. The fundamental role of domestic dogs in the epidemiological chain of VL was reaffirmed.

(1) Background: In orthognathic surgery, segmental Le Fort I osteotomies are a valuable method to correct maxillary deformities or transversal discrepancies. However, these procedures are technically challenging, and osteosynthesis can be prone to error. (2) Methods: In this retrospective, monocentric cohort study, patients were enrolled who underwent a virtually planned segmental maxillary osteotomy during their combined treatment. Positioning and osteosynthesis were achieved by either a 3D-printed splint and conventional mini plates or Patient-Specific Implants (PSI). The preoperative CT data, virtual planning data, and postoperative CBCT data were segmented. The deviation of all segments from the desired virtually planned position was measured using the analysis function of the IPS Case Designer. (3) Results: 28 Patients in the PSI Group and 22 in the conventional groups could be included. The PSI group showed significantly lower deviation from the planned position anteroposteriorly (-0.63±1.62mm vs. -1.3±2.54mm) and craniocaudally (-1.39±1.59mm vs. -2.7±3.1mm). For rotational deviations, the Pitch (0.64±2.59° vs. 2.91±4.08°) as well as the inward rotation of the lateral segments was positively influenced by PSI. (4). Conclusions: The presented data show that patient-specific osteosynthesis significantly reduces deviations from the preoperative plan in virtually planned cases. Especially transversal expansions and vertical positioning can be addressed better.

The composites of heteropolyacids (H3PW12, H3PMo12) incorporated into amine-functionalized silica materials, were used for the first time as heterogeneous catalysts in the valorisation of glycerol (a large waste from biodiesel industry) by acetalization reaction with acetone. The polyoxotungstate catalyst H3PW12@AptesSBA-15 presented higher catalytic efficiency than the phosphomolybdate, with 97% of conversion with 97% of solketal selectivity, after 60 min at 25 °C, or 91% of glycerol conversion and the same selectivity, after 5 min, performing the reaction at 60 ºC. A relation of catalytic performance and acidity of the catalyst is here presented. Furthermore, the stability of the solid catalyst was investigated and discussed.

The ethanol extract (EE) prepared from the leaves of Tibouchina granulosa, and its fraction in ethyl acetate (fEA) were evaluated concerning their capacity to reduce inflammation in different experimental models. fEA was also studied concerning its chemical constituents. EE and fEA were assayed for their anti-inflammatory potential, using formalin-induced licking behaviour and carrageenan-induced inflammation into the subcutaneous air pouch (SAP) models. Reduction in polymorphonuclear cells (PMN) activation was performed in freshly isolated PMN. Chromatographic analysis of fEA was done by HPLC. Hispiduloside was isolated as the main constituent in fEA and its quantity was estimated to be 11.75% in fEA, 3.05% in EE, and 0.2% (w/w) in the plant. EE (30 mg/kg) significantly reduced the second phase of formalin-induced licking. fEA demonstrated a reduction in leukocyte migration into the SAP. EE and fEA drastically reduced cytokines (TNF-α, IL-1β, and IFN-γ), nitric oxide (NO) production, in vitro PMN migration induced by C5a and IL-8, and TNF-α and IL-1β gene expression. Taken together our data indicate that either ethanol extract or its fEA fraction from leaves of T. granulosa present an anti-inflammatory effect contributing to the pharmacological and chemical knowledge of this species and confirming the rationale behind its traditional use.

Ensuring the security of vertical applications in fifth-generation (5G) mobile communication systems and previous generations is crucial. These systems must prioritize maintaining the confidentiality, integrity, and availability of services and data. Examples of vertical applications include smart cities, smart transportation, public services, Industry 4.0, smart grids, smart health, and smart agriculture. Each vertical application has specific security requirements and faces unique threats within the mobile network environment. Thus, it is essential to implement comprehensive and robust security measures. This approach helps minimize the attack surface and effectively manage risks. This survey thoroughly examines mobile networks and their security challenges in vertical applications, shedding light on associated threats and potential solutions. Our study considers the interplay between security considerations in 5G, legacy networks, and vertical applications. We emphasize the challenges, opportunities, and promising directions for future research in this field and the importance of securing vertical applications in the evolving landscape of mobile technology.

Soil water infiltration is an important component of the hydrological cycle and it is best evaluated when the raindrop is impacted on the ground surface. For this reason, it is affected by changes in land use and occupation, and by the characteristics and physical-hydric properties of the soil. This study aimed to evaluate soil water infiltration in areas occupied with annual crops (soybean and corn) and pastures, in two watersheds of the Teles Pires River-MT, using simulated rainfall, physical models and principal component analysis. Infiltration rates were evaluated from simulated rainfall with an average intensity of 75 mm h-1, with 4 repetitions per region (upper, middle and lower) of the hydrographic sub-basins of the Caiabi and Renato rivers, and soil use with cover, without cover and disturbed. Soil tillage provided higher water infiltration rates into the soil, especially in pasture areas in the two hydrographic sub-basins. There were significant adjustments of the mathematical models to the infiltration rate data for all land use and land cover conditions. The soil attributes that most interfered with the infiltration rate were microporosity, soil density and total porosity in the crop areas of the middle Caiabi, and microporosity, clay content, total porosity and silt content in the areas farming at the source of the Renato River. The Horton and Philip models presented the best adjustments in the hydrographic sub-basins of the Renato and Caiabi and Renato rivers, being recommended for estimating the rate of water infiltration into the soil in different uses, coverages, and regions.

Background: Gait analysis systems offer invaluable insights for rehabilitation, yet their expense limits clinician access. We developed GAITWell®, a low-cost modular system for capturing spatiotemporal gait variables, and evaluated its measurement properties. Methods: The GAITWell® uses discreet binary sensors on interconnected boards to collect gait data, which is then analyzed using the DBSCAN algorithm on the Cartesian points from sensor outputs. Reliability was assessed using ICC2,1, standard error of the mean (SEM) and Bland-Altman plots. Validity was determined by comparing GAITWell® with the Qualisys Pro-Reflex system. Results: Participated 38 healthy adults, with an average age of 33.2 years (SD 13.0). Correlations between GAITWell® and the Qualisys system ranged from moderate to very high for most gait variables, with the exception of stride length, which demonstrated a low but significant correlation (r = .360, p &lt; .05). The ICC2,1 indicated moderate to good agreement for most gait variables. Stance and double support times, cadence, and base of support exhibited poor reliability, characterized by larger SEM and limits of agreement. Conclusions: Our findings indicate that the GAITWell® system is a promising tool for gait analysis. Future research will enhance sensor accuracy and refine algorithms to improve reliability.

Here, one hundred patients (50 smokers and 50 non-smokers) clinically diagnosed with COVID-19 were studied. Yet, bioinformatics was used to predict epitopes on Tobacco mosaic virus coat protein (TMV-CP) to produce antibodies towards SARS-CoV-2. Death was three times higher in non-smokers than in smokers. However, biochemical parameters did not separate the groups. Bioinformatics analysis predicted the presence of B-cell epitopes in TMV-CP, suggesting the production of antibodies anti-TMV-CP in smoker patients. Smokers may develop severe forms of COVID-19, but survival was superior in the evaluated group than in non-smokers. Anti-TMV-CP antibodies, potentially present in smokers, might act as a pro-immune agent against SARS-CoV-2 at earlier stages of infection. These data are helpful for future studies assessing COVID-19 in smokers.

This study aimed to conduct a cross-cultural adaptation of the development of the cat-owner/dog-owner relationship scales. The method encompassed several stages: conceptual, item, semantic, operational, measurement, and functional equivalence. Processes included translations, synthesis of translations, back-translations, consensus on the English versions, external evaluation by the original authors, expert committee evaluation, and pre-tests. The study involved surveying 342 pet owners throughout Brazil using a 20-item questionnaire. Data analyses utilized confirmatory factor analysis, covariance-based modeling, and multigroup analysis. The techniques confirmed that the scale preserved its psychometric properties and showed no variance between dog and cat owners, indicating that the measured constructs are universal and unaffected by specific cultural nuances. Hence, the cross-cultural adaptation and validation of the scale facilitate applying and testing concepts and measures in diverse contexts, enriching our understanding of the dynamics between owners and their pets (dogs and cats) in different living situations. In addition, this research holds particular significance in Brazil, given the country’s vast cultural diversity.

Purpose: This study aimed to evaluate the nanomechanical properties and chemical composition of restorative materials and dental surfaces using different toothpastes. Methods: Enamel (n=60) and dentin (n=60) bovine blocks were obtained and restored using resin-modified glass ionomer cement (RMGIC, n=30) or composite resin (CR, n=30) to form the dentin adjacent to RMGIC (DRMGIC), enamel adjacent to RMGIC (ERMGIC), dentin adjacent to CR (DCR), and enamel adjacent to CR (ECR). After restoration, one hemiface of each specimen was coated with an acid-resistant varnish to create the control (C) and eroded (E) sides (erosion: 5 days, 4 × 2 min/day; 1% citric acid / abrasion: 2 × 15 s followed by immersion on slurries 2 min). Three toothpastes were used: without fluoride (WF; n=10), sodium fluoride (NaF; n=10), and stannous fluoride (SnF2; n=10). The specimens were analyzed for nanohardness (H), elastic modulus (Er), and chemical composition using energy-dispersive X-ray spectroscopy (EDS) and Raman microscopy. Data were analyzed using ANOVA two-way repeated measures and Tukey’s test (α = 0.05). Results: The NaF presented lower values of H for DRMGIC-C, with a statistical difference for WF (p < 0.05). SnF2 resulted in lower Er values for ERMGIC-E and RMGIC-E than WF and NaF (p < 0.05). WF showed lower calcium and phosphorus concentrations for DCR-E than other types of toothpastes (p < 0.05). Only stannous-based toothpaste damaged the elasticity of eroded glass ionomer restorations performed in enamel. Toothpastes with fluoride was capable for maintaining main chemical elements of dentin adjacent to restorative materials under challenge conditions.

Patients with chronic (CM) and high frequency episodic migraine (HFEM) report cognitive complaints that contribute to migraine burden. Although, there is little evidence about the ef-fects of migraine treatments on these symptoms. Objective: To evaluate the effect of preventive treatment on the impact of cognitive symptoms, specifically the ability to concentrate, in individuals with CM and HFEM. Methods: Prospective cohort study in patients with CM and HFEM initiating treatment with botulinum toxin (BT) or anti-CGRP/R monoclonal antibodies (mAbs). Patients were evaluated at baseline and after 3 months of treatment, using a headache diary and a question about the im-pact of migraine attacks on concentration (never, rarely, sometimes, often, and always). Results: 108 patients (105 females, 44.3 years of age on average), 75% with CM and 27% with HFEM were included, 55 received a first session of BT and 53 received 3 injections of a monthly mAb. In both groups, there was a significant decline on the impact of migraine in concentration (related samples Wilcoxon signed rank test <0.001) compared to baseline. Reduction in monthly headache days was the main predictor of any concentration improvement, while treatment group, age, ongoing medication with topiramate or baseline medication overuse were not sig-nificant. Conclusion: Preventive treatment of HFEM or CM with drugs not acting on central nervous sys-tem is associated with a decrease of the impact of migraine attacks on concentration, predicted by the decline in headache days. These results indicate that migraine preventive treatment also improves non-pain symptoms, which is relevant given the contribution of cognitive complaints to the impact of headache attacks

Leishmania parasites present astonishing adaptative abilities that represent a matter of life or death within disparate environments during the heteroxenous parasite life cycle. From an evolutionary perspective, organisms develop methods of overcoming such challenges. Strategies that extend beyond the genetic diversity have been discussed and include variability between parasite cells during the infections of their hosts. The occurrence of Leishmania subpopulation fluctuations with variable structural genomic contents demonstrates that a single strain might shelter the variability required to overcome inconsistent environments. Such intrastrain variability provides parasites with an extraordinary ability to adapt and thus survive and propagate. However, different perspectives on this evolution have been proposed. Strains or species living in the same environment can cooperate but also compete. These interactions might increase the replication rate of some parasites but cause the loss of more aggressive competitors for others. Adaptive responses to intra- and interspecific competition can evolve as a fixed strategy (replication is adapted to the average genetic complexity of infections) or an optional strategy (replication varies according to the genetic complexity of the current infection). This review highlights the complexity of interspecies and intrastrain interactions among Leishmania parasites as well as the different factors that influence this interplay.

Autosselecionar a intensidade do treinamento aeróbico é uma perspectiva que permite aos praticantes desenvolver autonomia (escolha do ritmo), melhorar a aptidão física e alcançar a perda de peso. Comparar o efeito de quatro protocolos de treinamento aeróbico nas respostas cardiometabólicas e psicofisiológicas em homens e mulheres adultos fisicamente inativos. A amostra foi composta por 11 indivíduos com idade entre 56 ± 10 anos e IMC 29,2 ± 2,4 kg/m2 que realizaram quatro diferentes protocolos de treinamento aeróbio em esteira, sendo: 1-indivíduo com intensidade autosselecionada (ISS), 2-indivíduo com intensidade prescrita (IPI) (64-76% da FC máx), grupo 3 pequeno com autosseleção. intensidade selecionada (SGS) e intensidade prescrita em 4 pequenos grupos (SGP) (64-76% da FC máx). Foram analisados ​​frequência cardíaca, lactato, percepção subjetiva de esforço, resposta afetiva, escala de ativação, prazer, intenção de repetir a sessão, velocidade da esteira e distância total do protocolo. A análise estatística utilizou ANOVA com teste post hoc de Tukey (p<0,05). As análises de frequência cardíaca, lactato, percepção subjetiva de esforço, escala de ativação, prazer, velocidade média e distância total não apresentaram diferenças significativas entre os protocolos. A resposta afetiva apresentou menor declínio no protocolo ISS (p<0,05), e a intenção de repetir a sessão de treinamento foi maior no protocolo ISS (p<0,05). Conclusão: Os dados permitem concluir que o protocolo de treino ISS produziu resultados superiores na resposta afetiva e na intenção de repetir a sessão.

For a long time, a company's Product Development Process (PDP) was seen as supporting the operations department, although PDP decisions and mistakes have a considerable impact on market performance. This is critical even in agriculture where bad habits and practices in the PDP can lead rural producers to great losses. Therefore, this research investigated the effect on the market performance of rural products (banana) in the southern region of Brazil, based on two analyses: (i) how sustainability practices support the PDP phases and (ii) how the phases of the Product Life Cycle Assessment (LCA) mediate sustainability practices and PDP phases. This study presents a quantitative analysis using Confirmatory Factor Analysis (CFA) and hierarchical ordinary least squares (OLS) regression of data obtained from a survey of 110 rural producers who directly participate in the banana production and planning process in southern Brazil. Our results shows that sustainability practices support the PDP, and we confirm that the product development and post-development phase has an effect on market performance. In addition, we identified that in the pre-development phase of the PDP, dealing with rural products (bananas), the maturity stage of the LCA mediates sustainability. In the PDP development phase, we concluded that rural families that develop economic and environmental practices with their products in the market growth phase may have reduced results. As for the post-development phase of the PDP, we conclude that when companies invest in environmental and social practices, there is a complete mediation of the effect, where these practices lose strength if the product is in the introduction and maturity phases in the market. As originality, our study contributed to demonstrate value on the product life cycle for the product development process in agriculture using sustainability practices through a systemic approach, filling the gap in the literature due to the lack of research on these areas seen in an integrated way.

Avipoxvirus (APV), a linear dsDNA virus belonging to the subfamily Chordopoxvirinae of the family Poxviridae, infects more than 278 species of domestic and wild birds. It is responsible for causing the avian pox disease, which is characterized by its cutaneous and diphtheric forms. With a high transmission capacity, it can cause high economic losses and damage to the ecosys-tem. Several diagnostic methods are available and vaccination of birds can be an effective pre-ventive measure. To update the molecular characterization and phylogenetic analysis of viruses isolated in Portugal between 2017 and 2023, ten APV-positive samples were analyzed. A P4b gene fragment was amplified by PCR and the nucleotide sequence of the amplicons was deter-mined by Sanger sequencing. The sequences obtained were aligned using ClustalW, and a max-imum likelihood phylogenetic tree was constructed. With this study, it was possible to verify that the analyzed sequences are distributed in subclades A1, A2, B1, and B3. Since some of them are quite similar to others from different countries and obtained in different years, it is possible to conclude that there have been several viral introductions in Portugal. Finally, it was possible to successfully update the data on avipoxviruses in Portugal.

The exponential growth in the consumption of electronics, in combination with the reduction in their useful life, leads to a significant increase in the volume of electronic material discarded. Printed Circuit Boards (PCBs) are modules composed of ceramic, polymer and metallic materials of high economic value and with a great potential for damage to biotic and anthropic environments when inadequately discarded. The aims of this work was to study the main environmental impacts and the efficiency of mechanical operations in the electronic waste recycling process in optimizing the concentration of metallic copper. For this, the samples obtained were characterized according to their morphology and chemical composition, and subjected to physical and mechanical treatments: dismantling, grinding, separation by granulometry, density and magnetic property. The environment impacts were estimated by the Life Cycle Assessment of the pre-treatment processes, associated with copper extraction operations in WPCBs. According to the results obtained, it is possible to infer that the NM +1mm Concentrated product presents in its metallic composition around 78% of copper, which contributes to the efficiency of the hydrometallurgical extraction processes. It is noteworthy that the Concentrated class represents about 14% of copper (wt) taking into account the amount of 3.789 kg of PCB waste input material. The potential for reinsertion of the dust in the material recovery process is highlighted, given that the chemical composition of this particulate has a significant presence of metals. In general, it was found that due to the higher concentration (wt %) of the sample being allocated in the range of - 0.15mm + 0.05mm, the elements Fe (18.30%), Si (10.73%), Ca (9.21%) and Cu (8.89%) stand out regarding the participation of the elemental composition of this fraction and also regarding the general composition of the sample. Furthermore, the generation of dust during the fragmentation process, can be associated with occupational respiratory diseases when not managed. About the Life Cycle Assessment, in seven of the nine categories evaluated, crushing and screening activities accounted for more than 90% of the recorded impact values. In general, it is estimated that in the pre-treatment phase be generated 15.4 kg CO2 eq.

The most relevant fungal disease of the olive tree in Portugal is anthracnose, which has negative effects on fruit destruction and consequently on the yield and quality of the olive oil. Moreover, the loss of quality caused by olive fruit fly is associated with the presence of fungi in the galleries made by the larvae. The present study focuses on the effect of olive anthracnose and olive fly on the content of bioactive compounds, namely on hydroxytyrosol (HYT) and its derivatives (health claim) in olive oils extracted from 'Galega Vulgar' and 'Cobrançosa' cultivars. The olives, with different damage levels (olive fly and anthracnose disease), were harvested in Castelo Branco (Center of Portugal) in organic rainfed orchards, at four harvest times during 2019, 2020 and 2021 harvest years. The fruits were immediately submitted to olive oil extraction. The results of the quality criteria show that Galega olive oils extracted from olives with a higher anthracnose incidence show no conformity for the Extra Virgin Olive Oil (EVOO) and Virgin Olive Oil (VOO) categories, with high acidity values and negative sensory notes accompanied by the disappearance of oleacein (the main phenolic compound of both monovarietal olive oils). Conversely, no sensory defects were observed in Cobrançosa olive oils extracted from fruit with high anthracnose and olive fly incidence. Moreover, despite a decrease in all the positive attributes associated with the cultivar, namely in oleacein and oleocanthal contents, quality criteria were still in accordance with the EVOO category. The total HYT and tyrosol (TYR) content (&gt; 5 mg/20g) allows the use of the health claim on the label of all the analysed Cobrançosa olive oils.

The regulation of multiple bacterial phenotypes was found to depend on different cyclic di-nucleotides (CDNs) that constitute intracellular signalling second messenger systems. Most notably, c-di-GMP, along with proteins related to its synthesis, sensing and degradation, was identified as playing a central role in the switching from biofilm to planktonic modes of growth. Recently, this world has been under expansion, with the discoveries of other signalling CNDs in bacteria (c-di-AMP and cGAMP) and also in eukaryotes, novel protein and RNA receptors of CDNs, and the numerous functions related to these molecules. In this work, we comprehensively review and analyse the structural biology data about the systems that bacteria use to synthesise and recognise CDNs, detailing their interactions at molecular level with their products/ligands. Additional interesting observations were made, including that different receptor types can bind CDNs in similar conformations and that, based on genomic data, different CDN second messenger systems may coexist in many organisms. The large amount of sequence and structural data available allows a broad view of the importance of CDNs in bacteria, but how cells coordinate these molecules to ensure adaptation to changing environmental conditions is still open for much further exploration.

Plant responses to different light and water availability are variable among species and their re-spective phenotypic plasticity, and the combination between these two abiotic factors can alleviate or intensify stressful effects. This study aimed to evaluate the impacts of exposure time of Cedrela fissilis Vell. seedlings to different water and light availability and the interaction of these factors. Seedlings were submitted to combinations of three shading levels – SH (0, 30 and 70%) and three water regimes based on the water holding capacity (WHC) in the substrate, constituting nine cul-tivation conditions: T1 – 0% SH + 40% WHC; T2 – 0% SH + 70% WHC; T3 – 0% SH + 100% WHC; T4 – 30% SH + 40% WHC; T5 – 30% SH + 70% WHC; T6 – 30% SH and 100% WHC; T7 – 70% SH + 40% WHC; T8 – 70% SH +70% WHC; T9 – 70% SH + 100% WHC. C. fissilis seedlings respond to water deficit, here represented by 40% WHC, regardless of exposure time, and when cultivated in full sun, the stressful effects were enhanced, acting in a synergistic manner. The condition that provided better gas exchange performance and greater total dry mass accumulation for C. fissilis seedlings was 30% shading combined with 100% WHC. C. fissilis seedlings have physiological plasticity and resilience to survive under different water and light conditions.

We demonstrate for the first time efficient mechanical to electrical energy conversion using InGaN/GaN nanowires (NWs). Using an atomic force microscope equipped with a modified Resiscope module, we analyse the piezoelectric energy generation of GaN NWs and demonstrate an important enhancement when integrating in their volume a thick In-rich InGaN insertion. The piezoelectric response of InGaN/GaN NWs can be tuned as a function of the InGaN insertion thickness and position in the NW volume. The energy harvesting is favoured by the presence of a PtSi/GaN Schottky diode which allows to efficiently collect the piezo-charges generated by InGaN/GaN NWs. Average output voltages up to 330 ± 70 mV and a maximum value of 470 mV per NW has been measured for nanostructures integrating 70 nm-thick InGaN insertion capped with a thin GaN top layer. This latter value establishes an increase of about 35% of the piezo-conversion capacity in comparison with binary p-doped GaN NWs. By considering these output signals, we estimate a maximum power density generated by one layer of dense InGaN/GaN-based NW of about 3.3 W/cm². These results settle the new state-of-the-art for piezo-generation from GaN-based NWs and offer a promising perspective for extending the performances of the piezoelectric sources.