Access to good nutritional health is one of the principal objectives of current society. Several e-services offer dietary advice. However, multifactorial and more individualized nutritional recommendations should be developed to recommend healthy menus according to the specific user's needs. In this article we present and validate a personalized nutrition system based on an application (APP) for smart devices with the capacity to offer an adaptable menu to the user. The APP was developed following a structured recommendation generation scheme, where the characteristics of the menus of 20 users were evaluated. Specific menus were generated for each user based on their preferences and nutritional requirements. These menus were evaluated by comparing their nutritional content versus the nutrient composition retrieved from dietary records. The generated menus showed great similarity to those obtained from the user dietary records. Furthermore, the generated menus showed less variability in micronutrient amounts and higher concentrations than the menus from the user records. The macronutrient deviations were also corrected in the generated menus, offering a better adaptation to the users. The presented system is a good tool for the generation of menus that are adapted to the user characteristics and a starting point to nutritional interventions.

Zn is an essential element for children related to optimal growth, development and nutritional metabolism. We measured Zn bioaccesibility (Zn-BA) levels of foods by Inductively coupled plasma mass spectrometry (ICP-MS) after in vitro digestion-fermentation method from children with gluten related disorders (GRD-CH), obesity (OB-CH) and allergy/intolerance to cow’s milk proteins (AICM-CH). Zn-BA levels in sick children (34.7 ± 28.8, 29.6 ± 30.1 and 26.7 ± 30.4%, respectively) were significantly lower (p < 0.05) than in healthy norm-weight children (HE-CH). For AICM-CH, Zn-BA in animal foods was significantly lower than in plant foods, and in both plant and animal foods from sick and healthy children (p < 0.05). In foods of animal origin in sick and healthy children, Zn-BA in foods heated in liquid media (frying and boiling) was significantly higher than in foods heated by hot air (roasting and grilling). In conclusion, in children the studied diseases diminished the Zn-BA, probably by the alteration of the gut microbiota which could negatively affect their appropriate long-term development. In AICM-CH, the allergy to cow's milk proteins could induce intestinal dysbiosis and inflammatory processes, leading to allergies to other animal food proteins, and to a more pronounced decrease of Zn-BA.

We report recent enhancements of the online atomic database at the Ohio State University, NORAD-Atomic-Data, that provides various parameters for radiative and collisional atomic processes dominant in astrophysical plasma. NORAD stands for Nahar Osu RADiative. The database belongs to the data sources, especially for the latest works, of the international collaborations of the Opacity Project and the Iron Project. The contents of the database are calculated values for energies, oscillator strengths, radiative decay rates, lifetimes, cross sections for photoionization, electron-ion recombination cross sections and recombination rate coefficients. We have recently expanded NORAD-Atomic-Data with several enhancements over those reported earlier. They are as follows. i) We continue to add energy levels, transition parameters, cross sections for atoms and ions with their publications. ii) Recently added radiative atomic data contains significant amount of transition data for photo-absorption spectral features corresponding to x-ray resonance fluorescence effect, prominent wavelength regions of bio-signature elements, such as phosphorus ions, and emission bumps of heavy elements, such as of lanthanides, that may be created in a kilonova event. We are including iii) collisional data for electron-impact-excitation, iv) experimental data for energies and oscillator strengths for line formation, v) experimental cross sections for photoionization that can be applied for benchmarking and other applications, and vi) introduction of a web-based interactive feature to calculate spectral line ratios at various plasma temperature and density diagnostics, starting with our recently published data for P II. We presented summary description of theoretical backgrounds for the computed data in the earlier paper. With introduction of experimental results, we present summary description of measurement of high resolution photoionization cross sections at Advanced Light Source of LBNL synchrotron set-up and briefly discuss other set-ups. These additions should make NORAD-Atomic-Data more versatile for various applications. For brevity, we provide information on the extensions and avoid repetition of data description of the original paper.

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

Introduction: The transcranial direct current stimulation (tDCS) is a promising technique for brain modulation after cerebrovascular accident (CVA). This treatment modality has been previously studied in the recovery of patients. The aim of this review is to analyze the evidence in the ap-plication of tDCS in the recovery of gait disturbance in stroke patients. Methods: This review was conducted according to the recommendations of the PRISMA statement. Three different elec-tronic databases were searched for relevant results: PubMed, Scopus, and Cochrane. We included reviews and meta-analyses that only considered randomized controlled trials (RCTs) that inves-tigated the effects of transcranial direct electrical stimulation, in combination or not with other physiotherapy treatment, on gait recovery. Results: Thirteen studies with a total of 195 RCTs were included. Data on population, outcome measures, protocols and outcomes were extracted. The Amstar-2 scale and the GRADE system of certainty of evidence were used. Only one study re-ceived high certainty of evidence, 5 received low certainty of evidence and 7 received critically low certainty of evidence. Conclusions: Although the tDCS produces positive changes in gait recovery in spatio-temporal parameters, mobility, endurance, strength and motor function, there is insuf-ficient evidence to recommend this treatment.

Daniel Yergin’s “The New Map: Energy, Climate, and the Clash of Nations” is a remarkable and groundbreaking work that addresses the ever-changing global energy landscape and its profound geopolitical implications. In this modest book review, we aim to offer a fresh perspective by re-examining the core issues from the standpoint of political geography. The aim of this article is twofold: to enrich the existing literature on political geography and to provide valuable insights to students of geography to broaden their knowledge in this field.

The storm 'Daniel' has caused the most severe flood phenomenon that Greece has ever experienced, with thousands of hectares of farmland submerged for days. This led to sediment deposition in the inundated areas, which significantly altered the chemical properties of the soil, as revealed by extensive soil sampling and laboratory analysis. Causal relationships between soil chemical properties and sediment deposition were extracted using the DirectLiNGAM algorithm. Results of causality analysis showed that the sediment deposition affected the CaCO3 concentration in the soil. Also, causal relationships were identified between CaCO3 and available phosphorus (P-Olsen), as well as between sediment deposit depth and available manganese. The quantified relationships between the soil variables were then used to generate data using a Multiple Linear Perceptron (MLP) regressor for various levels of deposit depth (0, 5, 10, 15, 20, 25 and 30 cm). Then linear regression equations were fitted across the different levels of deposit depth to determine the effect of deposit depth on CaCO3, P, and Mn. The results show that there is a linear slope of 0.12, -0.16, and 0.13, for CaCO3, P, and Mn with deposit depth, respectively. Statistical analysis indicates that corn growing in soils with sediment over 10 cm requires a 31.8% increase in P rate to prevent yield decline. Additional notifications regarding cropping strategies in the near future are also discussed.

This paper critically reviews the convergence between Business Ecosystem Theory and Social Network Theory in sustainability studies. While both frameworks view organizations as part of larger, interconnected systems, they can be differentiated by six key dimensions: unit of analysis, focus, decomposability, types of relationships, market segment, and worldview. To better reflect real-world phenomena, this paper argues for a new stream of theoretical convergence that is practical, reliable, generalizable, and reproducible. Specifically, it proposes shifting from interoganizational networks to interfunctional networks, which reduces complexity, enhances stability over time, and provides a clearer theoretical distinction. This is illustrated through a case study of Tesla Inc.’s ecosystem, built from data presented in the company’s 10K form, which also serves as an example of the emergence of a new strategic construct named the Business Ecosystem Footprint. This construct could assist managers in understanding where their organization stands within the network of functions, guiding them in making informed decisions about resource allocation and diversification, specifically aimed at supporting financial goals as well as sustainability and decarbonization objectives. The article concludes by suggesting potential research agendas, such as automating ecosystem mapping, exploring the constraints of the new construct, and testing new hypotheses related to firm performance.

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in the Amazon. Images from medium-resolution optical satellites (mostly Landsat) combined with extensive field data have allowed researchers to assess patterns of tree mortality and monitor forest recovery over decades of subsequent succession in different regions. Although satellites with high spatial-resolution have become available for the Amazon in the last decade, they have not yet been employed for the mapping and quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November/2015. Remote sensing estimates of tree mortality were produced with Spectral Mixture Analysis and analyzed together with forest inventory data using Generalized Linear Models. Windthrow tree-mortality measured in 3 transects (30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Based on this ground truth, the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3% windthrow tree-mortality, p<0.001). The mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of fit of models showed the opposite pattern, which may reflect the influence of crown damage not accounted for in our field study, and fast-growing regeneration of leaf area. Among the satellites studied, Landsat 8 most accurately captured field observations of variations in tree mortality across the disturbance gradient (i.e., lower under- and/or overestimation from undisturbed to extremely damaged forest). Although satellites with high spatial-resolution can refine estimates of windthrow severity by allowing the quantification of individual tree damage and mortality, our results validate the reliability of Landsat imagery for assessing patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Although high-resolution imagery may improve estimates of tree damage and mortality, these should be validated using field data at compatible scales.

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

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

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

The COVID-19 pandemic has become the largest public health crisis since the 1918 influenza pandemic. Despite the extensive research conducted on the SARS-CoV-2 virus in humans, little is still known about animal-related transmission and its consequences. Therefore, this study contributed to a better understanding of this issue by focusing on the serological survey of SARS-CoV-2 in samples from the serum bank of the Bovine Virology Laboratory at the Biological Institute of São Paulo, as well as horses and dogs from the Military Police of the State of São Paulo, and tapirs and bats from the states of Mato Grosso do Sul and São Paulo. To achieve this, the possible presence of anti-SARS-CoV-2 antibodies in domestic and wild animal species was evaluated using the ID Screen® "SARS-CoV-2 Double Antigen Multi Species" ELISA test (ID-Vet.®), following the manufacturer's recommendations. The findings of this study demonstrate a higher occurrence of anti-SARS-CoV-2 antibodies in domestic animals compared to wild animals, as well as different antibody profiles among the species analyzed, with horses showing a wide range of seroconversion comparable to humans.

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

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

Heat shock proteins (Hsps) are highly conserved molecules that are constitutively expressed and upregulated in response to physiological stress conditions. These immunogenic chaperones can have essential functions in fungi, particularly in dimorphic pathogens. Histoplasma capsulatum and Paracoccidioides species are dimorphic fungi that are the causative agents of histoplasmosis and paracoccidioidomycosis, respectively, which are systemic mycoses with significant rates of morbidity and mortality. Current treatment consists of long-term antifungal agents, and there is an urgent need for new therapeutic approaches with higher efficacy, lower toxicity, better biodistribution and improved selectivity. We engineered an immunoglobulin G1 (IgG1) isotype chimeric mouse-human monoclonal antibody, titled ch-MAb 4E12, from the parental IgG2a MAb 4E12, a monoclonal antibody to H. capsulatum Hsp60 that is protective in experimental histoplasmosis and paracoccidioidomycosis models elicited by H. capsulatum var. capsulatum and Paracoccidioides lutzii, respectively. The ch-MAb 4E12 increased phagolysosomal fusion and enhanced the yeasts uptake by PMA differentiated human THP1 macrophage cells in vitro. At low concentrations, the chimeric antibody significantly reduced the pulmonary and splenic fungal burden compared to an irrelevant antibody or no treatment. These results are the first to show that a chimeric mouse-human antibody can modify infection caused by dimorphic fungi.

In southern South America, zonal flora, defined by macroclimatic conditions, is strongly influenced by an aridity filter near 29°S. Cushion bogs, high-altitude wetlands along the Andes, display homogeneous flora with cushion species dominance, contrasting with zonal vegetation. Despite being influenced by microclimatic conditions, these ecosystems experience varied environmental effects. This study identifies environmental filters affecting bog communities along a broad-scale latitudinal gradient from 15°S to 42°S. We analyzed 420 bogs and 284 species across three macroclimatic regions with distinct summer, winter, and transitional arid rainfall regimes. Using variance partitioning and membership-based regionalization models, we examined the impacts of climatic, edaphic, and spatial variables on beta diversity. We also assessed species' niche overlap and the influence of environmental filters on the communities' phylogenetic diversity. Results show that species turnover and niche overlap vary with macroclimatic differences, delineating three distinct regions. Notably, phylogenetic clustering in the driest part of the gradient (23°S —24°S) highlights the impact of the environmental filter. Aridity and temperature variations at a broad scale serve as environmental filters shaping the composition of bog communities across southern South America.

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

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

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

We propose an advanced filtering scheme based on Recurrent Neural Networks (RNNs) and Deep Learning to enable efficient control strategies for Vertical Farming (VF) applications.  We demonstrate that the best RNN model incorporates five neuron layers, with the first and second containing ninety Long Short-Term Memory neurons.  The third layer implements one Gated Recurrent Units neuron.  The fourth segment incorporates one RNN network, while the output layer is designed by using a single neuron exhibiting a rectified linear activation function.  By utilizing this RNN digital filter, we introduce two variations: (1) A scaled RNN model to tune the filter to the signal of interest, and (2) A moving average filter to eliminate harmonic oscillations of the output waveforms. The RNN models are contrasted with conventional digital Butterworth, Chebyshev I, Chebyshev II, and Elliptic Infinite Impulse Response (IIR) configurations.  The RNN digital filtering schemes avoid introducing unwanted oscillations, which makes them more suitable for VF than their IIR counterparts.  Finally, by utilizing the advanced features of scaling of the RNN model, we demonstrate that the RNN digital filter can be pH selective, as opposed to conventional IIR filters.

In recent years, many libraries and archives have started digitizing their collections thus making maps by Indigenous peoples more easily available for scholars to study. While a number of these maps were discussed by G. Malcolm Lewis in the History of Cartography series (volume 2, book 3, Chapter 4: 1984), more have since been found and disseminated. These maps are critical in understanding the historic and current land tenure of Indigenous groups. Further, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views resulting in the mistaken view that Natives did not have formal concepts of their territories. Further, Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper will illustrate how many Native residents were very spatially cognizant of their own lands, as well as neighboring nations’ lands, overlaps between groups, hunting territories, populations, and trade networks. Currently, the Sinixt First Nation provides a perfect example of how an Aboriginal people are inputting and using a GIS representation of their territory with proper toponymy and use areas.

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

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

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

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

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

With the exponential growth of internet usage and mobile devices, the volume of user behavior data has surged, offering significant opportunities and challenges for businesses. This paper explores user behavior analysis in the context of big data, highlighting its pivotal role in driving innovation and strategic decision-making. We begin by discussing the importance of user behavior data and reviewing technological advancements such as machine learning, natural language processing, and data mining that enable deep insights into user behavior. Through a case study on linguistic analysis in livestreaming e-commerce, we demonstrate how text-mining techniques can correlate linguistic characteristics with sales performance, providing actionable marketing insights. We further explore the broader business applications, including personalized recommendations, user portraits, product design, and strategic decision-making. Technical and ethical challenges, such as data integration, privacy concerns, and algorithmic bias, are also addressed. The paper concludes with a discussion on future trends, such as AI and ML advancements, edge computing, IoT proliferation, and ethical AI frameworks, poised to shape user behavior analysis. Our findings underscore the transformative potential of user behavior data in enhancing business operations and user experiences, providing recommendations for future research focused on real-time analytics, privacy-preserving techniques, and ethical implications of data-driven decisions.

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

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

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

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

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

The survival rates of women with stage 0 or 1 breast cancer stands at almost 100% and around 93% for stage 2. As the disease advances with decreasing survival, the rate detoriates to 72% for stage 3 and about 22% for stage 4 (ACS, 2018). Undoubtedly, earlier presentation is synonymous with better prognosis and survival. In fact data indicates that early stage breast cancer diagnoses has 90% survival rate as compared to 27% for the advanced states (ACS, 2018). In this regard, governmental and non-governmental agencies are working tirelessly towards the realization of improved breast cancer care and survival through early presentation and detection. For instance, the Sustainable Development Goal (SDG) Target 3.4 seeks to reduce by one third, premature mortality from cancers and other non-communicable diseases through prevention and treatment. Clearly, early presentation, diagnoses and treatment will assist in the realization of the SDG target 3.4 goal. To achieve this, research must be focused on early presentation among women with breast cancer.. However, current studies have focused mainly on advanced breast cancer regarding treatment, symptoms experience (emotional and psychological), coping and support systems, and the reasons for delayed diagnoses and treatment. Objective In this review, it is argued that, rather than focusing on advanced breast cancer which has been adequately explored, the attention has to be on what measures or approaches promote early presentations among Ghanaian women. Methods The review included all primary studies that provided answers to the phenomenon of interest. It included both quantitative and qualitative studies. Search scope encompassed studies within the last ten years; thus from 2010 to 2020 irrespective of the country of study.Studies were included if: The paper is of a primary study; the study population included women with early BC or BC symptoms; the study outcome is the association between early stage breast cancer and earlier presentation; the study has a comprehensive data analysis protocol; the results of the studies are unique.A thorough literature search was conducted using the following electronic database: Google scholar and Pubmed. Google scholar alert on new studies was subscribed. This gave update on newly published papers for appraisal and possible inclusion.Manual identified of other potentially eligible publications by searching the reference lists of retrieved studies was also done. After a thorough search, this review included studies from several countries around the Globe such as Ireland, London, Turkey, Iran, Ghana, Kenya, Ethiopia etc Data Collection The title and or abstract of all retrieved papers were independently scanned through to establish which studies should be further evaluated. The full texts of these potential articles were then assessed. Extraction The Cochrane extraction form for data extraction was resorted to. From each eligible article, the following study identifiers/information were extracted: author(s), first author, year, title, objective, article type, location, setting, study design and method, sample size, instruments used, and results. Results Prompt help seekers mainly self-discovered their BC, and this occurred through accidental touch, after menstruation, through breastfeeding, during grooming, and while taking their bath.Notably, women who were termed prompt help seekers had higher seriousness perception of their symptoms. This was likened to their level of understanding and awareness, as well as periodic examination and comparison. Similarly, women who knew they were at risk for breast on account of family history, and increased incidence of BC in their localities, labeled their initial symptoms as requiring prompt attention.Following interpretation and labeling of symptoms, the participants generally resorted to symptom monitoring until the onset of additional and or intense symptoms. Though most women thought of benign growths, a few feared it could be malignant. These emotional reactions led the women to purposively seek clarification by selectively consulting others. Further, participants opened up to social acquaintances such as family relationships, people with prior experience of breast disease, and in some few instances health professionals. Some women also resorted to media items to better their understanding. Remarkably, prompt help seekers sort for help within one month. Last but not least, some women first communed with their creator after discovery and labeling based on their spiritual affiliations.Also, researchers should consider conducting surveys to assess the BC risks for specific smaller groups. This would help tailor specific educational interventions to promote earlier presentation and treatment among the vulnerable.

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

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.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

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

Groundwater is becoming increasingly important in the Pacific Northwest of the USA due to declining snowpack volumes and shifts in precipitation type and timing, all connected with climate change. The Upper Williamson Basin of the Klamath Watershed is a groundwater dominated watershed with massive fluctuations in year-to-year streamflow volumes over the past four decades, including the complete absence of any live flow for several years. The precise relationship between groundwater and streamflow in the basin has been difficult to assess due to a limited number of monitoring wells and significant gaps in the water level time history. To address this challenge, we use a novel imputation technique that leverages Earth observations and machine learning to impute gaps in water level records. We use these more complete datasets to compute a groundwater storage change time series for the basin. We show that groundwater storage is highly correlated to streamflow and that groundwater storage is correlated to rainfall with a three- to four-year delay that appears variable depending on groundwater storage volumes. The tools and relationships we present make it possible for water managers to estimate when streamflows will return to the basin and be more informed to support better management.

In modern times, technology has become more than just a tool; it is a vital component of our lives, driving society and humanity towards new horizons, better living standards, and solu-tions for complex, global challenges. This article explores the world of dependable systems, specifically focusing on system design, software solutions, and architectural decisions that fa-cilitate collaborative work. It aims to dive into the intricacies of designing robust and effective document collaboration software. Throughout this paper, readers will gain insights into the proposed design process, enabling them to understand, learn from, and critically evaluate the examined methodologies and outcomes. Like everything else in the software technology field, there are multiple solutions to any given problem, and this work is no exception to this rule. The objective of this study is to provide a detailed architectural overview of the microservices pattern in an orchestrated cloud environment based on independent containers. To examine the pros and cons of such a system, the paper will detail how a real-time document collaboration system can benefit from such an architecture regarding availability, elasticity, scaling, and disaster recovery. Moreover, the paper will analyze how cloud-native technologies can be used to create a scalable platform solution, capable of handling traffic, dynamic resource storage, asynchronous com-munication, and application scaling. The intricate nature of this system renders this paper a valuable resource for prospective investigations within the domain of dependable systems, cloud computing, and distributed systems. This paper not only showcases the design and implementation process but also sets a founda-tion for future research and innovation in dependable systems, collaborative technologies, sustainable solutions, and distributed system architecture.

The Iberian wolf (Canis lupus signatus) is recolonizing historical distribution areas after decades of absence. As in other human-dominated landscapes, finding a balance to protect this species by favoring recolonization and mitigating human-wildlife conflicts is a challenge. Since wolves are often generalist opportunistic predators, we studied their diet composition in the Central Spain to evaluate the consumption of domestic ungulates and provide reliable data that help local authorities to deal with the current wolf-cattle ranchers conflict and coexistence. Diet composition (% prey occurrence, % prey ingested biomass) was analyzed through the identification of prey hairs present in 671 scats collected between 2017 and 2021. Wolves fed more on wild ungulates (82% occurrence) than domestic ones (18%). Wild boar (Sus scrofa, 44% occurrence) and roe deer (Capreolus capreolus, 35%) were the most consumed prey. Wolves positively selected these two species. The wolf's diet varied between seasons, years, and forest regions, but a diet based on wild ungulates predominated over domestic ones. Food niche breadth and showed variations depending on seasons and years. Preserving the availability and diversity of wild ungulates may favor reducing livestock attacks and would be an achievable goal that help to conserve this species and reduce conservation conflicts.

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

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

Knowledge about the formation energies of compounds is essential to derive phase diagrams of multi-component phases with respect to elemental reservoirs. The determination of formation energies using common (semi-)local exchange-correlation approximations of density functional theory (DFT) exhibits well-known systematic errors if applied to oxide compounds containing transition metal elements. In this work, we generalize, reevaluate and discuss a set of approaches proposed and widely applied in the literature to correct for errors arising from the over-binding of the O2 molecule and from correlation effects of electrons in localized transition-metal orbitals. The DFT+U method is exemplarily applied to iron oxide compounds, and a procedure is presented to obtain U values, which lead to formation energies and electronic band gaps comparable to experimental values. Using such corrected formation energies, we derive the phase diagrams for LaFeO3, Li5FeO4 and NaFeO2, which are promising materials for energy conversion and storage devices. A scheme is presented to transform the variables of the phase diagrams from the chemical potentials of elemental phases to those of precursor compounds of a solid-state reaction, which represents the experimental synthesis process more appropriately. The discussed workflow of methods can directly be applied to other transition metal oxides.

G4v is a four-vector theory of gravitation proposed by Mead (2015, 2023a,b) which reinterprets several major results commonly celebrated for the tensor-based approach of General Relativity (GR). Here, we show that G4v obeys the correspondence principle, an important test of any relativistic theory. We derive the non-relativistic Lagrangian and Energy expressions at the limit of low speeds and potentials, complete with the correct terms for potential energy (something traditional Special Relativity is incapable of achieving). G4v could represent a new interpretation of the gravitational field with essentially the same mathematics as electromagnetism (Mead 2023a). It is also possible to interpret G4v as a very interesting (and useful) approximation of the Einstein field equations (Mead 2023b).

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

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

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

The present study investigates the impact of electrode surface roughness on the electrofreezing of water. This research focuses on how the electrode roughness induced by a laser treatment affects the nucleation and growth of ice crystals under controlled electric fields. To achieve this, a series of experiments were conducted using deionized water samples placed between electrodes with varying surface roughness. The electrodes, fabricated with the Al6061 T6 alloy were structured via the Laser Shock Processing (LSP) method. For this purpose, the pulsed densities during the LSP process were varied from 900 to 2500 pulses/cm2. The increase of the pulse density was correlated to the surface structuring and to the microstructural features and average roughness of the LSP-treated Al6061 alloy. A wavy-like microstructure was induced upon the LSP treatment with average roughnesses between ~ 3.5 and 6 µm at the selected pulse densities. The results indicate that electrode roughness significantly influences the electrofreezing process. Rougher electrodes were found to lower the nucleation temperature compared to smoother ones, suggesting enhanced ice nucleation activity. The findings are attributed to the increased electric field concentration at the asperities of the rough surfaces, which may facilitate the alignment of water molecules and the formation of critical ice nuclei.

Near-infrared spectroscopy (NIRS) has become a key modality in medical imaging, finding application in both brain and breast imaging. This paper discusses the current trends in NIRS for brain and breast imaging, exploring advances in multi-modal integration with modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Challenges related to spatial resolution, depth sensitivity, and the impact of extracerebral tissues on signal specificity are examined. In addition, ongoing efforts to enhance hemodynamic measurements’ quantitative accuracy. Challenges, including limited spatial resolution and tissue heterogeneity, are discussed. The discussion extends to diffuse optical tomography and ongoing instrumentation development, clinical trials and studies validating NIRS diagnostic efficacy in breast imaging. The paper emphasizes the need for standardization, integration into routine clinical practice, and motivates for future work.

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

It is well established the complex exponential and logarithm are multivalued functions, both failing to maintain most identities originally valid over the positive integers domain. Moreover the general case of complex logarithm, with a complex base, is hardly mentionned in mathematic litterature. We study the exponentiation and logarithm as binary operations where all operands are complex. In a redefined complex number system using an extension of the C field, hereafter named E, we prove both operations always produce single value results and maintain the validity of identities such as log_u (w v) = log_u (w) + log_u (v) where u, v, w in E. There is a cost as some algebraic properties of the addition and subtraction will be diminished, though remaining valid to a certain extent. In order to handle formulas in a C and E dual number system, we introduce the notion of set precision and set truncation. We show complex numbers as defined in C are insufficiently precise to grasp all subtleties of some complex operations, as a result multivaluation, identity failures and, in specific cases, wrong results are obtained when computing exclusively in C. A geometric representation of the new complex number system is proposed, in which the complex plane appears as an orthogonal projection, and where the complex logarithm and exponentiation can be simply represented. Finally we attempt an algebraic formalization of E.

Serendipity favors the prepared mind, but how does the brain make that lucky find? Analyzing the cerebral mechanisms behind an exceptional (albeit trivial) discovery, the author suggests that a combination of ‘concept cells’ and the Global Neuronal Workspace Hypothesis could explain how we make great discoveries.

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

This study presents a unique model for assessing the dependability of continuous parts of combined systems in open-pit mining through the application of fuzzy logic. Continuous sub-systems as part of the combined system of coal exploitation in surface mines have the basic function of ensuring safe operation, high capacity with high reliability and low costs. These subsystems are usually part of the thermal power plant's coal supply system and ensure stable fuel supply. The model integrates various independent partial indicators of dependability into an expert system specifically designed for evaluating these systems. It deconstructs the complex parameter of system dependability into distinct partial indicators: reliability, maintainability, and logistical support. These indicators are then integrated using fuzzy composition (max-min composition). Historical data from 2018 to 2023 is utilized alongside the fuzzy model to provide a retrospective analysis of system dependability, serving to validate the model's effectiveness. What sets this model apart from conventional approaches is its consideration of practical dependability indicators, thereby obviating the need for extensive long-term monitoring and data collection to portray the system's status accurately over time. This model serves as a valuable tool for assisting decision-makers in open-pit mining operations, facilitating planning, exploitation control, and the selection of maintenance strategies to ensure consistent production and cost reduction. Designed for quick assessment, the model relies on expert judgments and assessments to determine system dependability efficiently.

The advent of modern satellite technology has transformed observational astronomy and astrophysics, offering unprecedented insights into the large-scale behavior of gravitation and challenging established cosmological models. This technological progress has reinvigorated the study of relativistic cosmology, leading to a critical reassessment of foundational assumptions, particularly the cosmological principle, which posits that the universe is homogeneous and isotropic on large scales. While this principle underpins the Standard Cosmological Model and the Friedmann-Lemaitre-Robertson-Walker metric, emerging data has increasingly been challenging its validity. Central to this investigation are the redshift-distance and light intensity-distance relations, essential for testing cosmological models. The integration of both parametric and nonparametric redshift models provides a more comprehensive analysis, addressing discrepancies in our understanding of the universe's structure and evolution. However, unresolved mysteries, particularly concerning dark matter and dark energy, complicate these models. This research critically examines the cosmological principle using the latest observational data and scrutinizes the Friedmann model's assumptions. The study shows that galaxy formation was most rapid in the early universe, especially within the redshift range of , with notable peaks around at and These two characteristic redshift values, predicted by our standard Friedmann redshift model used in this work, are confirmed by the observational data utilized in this research. The research also highlights that dark matter plays a significantly more critical role than dark energy in the process of galaxy formation. While dark energy primarily affects the large-scale expansion of the universe, dark matter seems to go beyond the domination of local galaxy formation and evolution of cosmic structures. These findings underscore the limitations of current models and contribute to the ongoing refinement of cosmological theories, offering a clearer understanding of the universe’s evolution.

The existence of the exclusion zone (EZ), a layer of water in which plastic microspheres are repelled from hydrophilic surfaces, has now been independently demonstrated by several groups. A better understanding of the mechanisms which generate EZs would help with understanding the possible importance of EZs in biology and in engineering applications such as filtration and microfluidics. Pollack theorizes that EZ water exists in a new phase which has a layered structure. We note several problems with Pollack's proposed structure, some of which were noted in the 1960's when a similar structure was proposed for ``polywater''. We argue that Schurr's diffusiophoresis based theory presents a compelling alternative explanation for the core EZ phenomena, although there remain other findings from Pollack's lab it does not explain. Among other things, Schurr's theory makes predictions about the growth of the EZ with time which have been confirmed by Florea et al.\ and others. In this work we also introduce and explore a novel hypothesis - that some aspects of EZ phenomena may be attributable to repulsive van der Waals forces. Finally, we touch on several possible confounding factors that make experimentation on EZs difficult, such as charged surface groups, dissolved solutes, and adsorbed nanobubbles.

The Golgi apparatus (GA) dysfunctions in Parkinson’s Disease (PD), neurodevelopmental disorders (NDDs), cancer, and organelle structural biology (OSB) can provide insights into therapeutic targets, gene therapy, and drug design. Primary defects and fragmentation within the GA are implicated in a wide range of neurodegenerative diseases. GA defects typically result in mislocation of proteins, accumulation of undegraded proteins, and impaired glycosylation of proteins. Inhibition of vesicular trafficking by α-synuclein (aSyn) may affect the dopamine-producing neurons and neuromodulators. GA regulates apoptosis during pathological mechanisms of neurological diseases and could provide new avenues in treatments through translation research. PD patients bearing the hereditary E46K disease mutation manifest the clinical picture of parkinsonism. How do we provide high resolution nanoimages of the GA during disease to capture dysfunction? Could we visualize the aSyn traffic jam between vesicles in the organelles ER and GA? OSB is emerging as a field as more technology advances and is more accessible. Structural studies of the GA will advance the field of neurological disease forward with an in depth understanding of dysfunction, fragmentation, and defects. Discoveries of the GA in PD, NDDs, and cancer would break new ground and provide translational medicine data of these diseases. Future research could be visualizing high angle annular dark field-STEM (HAADF-STEM) tomograms, cryogenic electron tomography (cryo-ET), multiplex correlative light and electron microscopy (cryo-CLEM), nanobody-assisted tissue immunostaining for volumetric EM (NATIVE) and using soft X-ray tomography (SXT) and computational reconstruction of the GA.

Multiple social and environmental justice concerns are linked to urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. This study used 1m resolved LIDAR data to characterize land use in Salt Lake County, Utah and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non irrigated cover, increased built cover, and higher amounts of households living under poverty was related to higher long-term PM2.5 exposure. Several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research grade air quality sensors.

Mangroves and salt marshes are among the most productive ecosystems in the global coastal ocean. Mangroves store more carbon (739 Mg CORG ha-1) than salt marshes (334 Mg CORG ha-1), but the latter sequester proportionally more (24%) net primary production (NPP) than mangroves (12%). Mangroves exhibit greater rates of gross primary production (GPP), above-ground net primary production (NPP) and plant respiration (RC) with higher PGPP/RC ratios, but salt marshes exhibit greater rates of below-ground NPP. Mangroves have greater rates of subsurface DIC production and, unlike salt marshes, exhibit significant microbial decomposition to a soil depth of 1 m. Salt marshes release more soil CH4 and export more dissolved CH4 , but mangroves release more CO2 from tidal waters and export greater amounts of POC, DOC and DIC to adjacent waters. Both ecosystems contribute only a small proportion of GPP, RE (ecosystem respiration) and NEP (net ecosystem production) to the global coastal ocean due to their small global area, but contribute 72% of air-sea CO2 exchange from the world’s wetlands and estuaries and contribute 34% of DIC export and 17% of DOC + POC export to the world’s coastal ocean. Thus, both wetland ecosystems contribute disproportionately to carbon flow of the global coastal ocean.

Large ruminant production is associated with high greenhouse gas emissions (GHGe) intensity, with the highest in southeast Asia being Laos at 102.9 CO2eq/kg meat produced, compared with average global meat emissions intensity of 33 CO2eq/kg. As recent studies in Laos identified emissions control molasses blocks (ECBs) achieved abatement of 470kg CO2eq/20kg block consumed, a study was conducted with a supplement mix with reported methane reducing properties, containing plant tannins and citral extract, salt, molasses and water. Groups of housed dairy buffalo (n=7) and pasture-fed grazing beef cows (n=11) were randomly selected, body condition scores estimated (BCS:1-5) and baseline nasa-oral methane eructation measured daily for 2 weeks. All animals were offered 300-400g/day of the mix for a month, with buffalo accessing abundant fresh cut forages whereas the grazing cows accessing rice straw and pasture declining in quality and quantity due to severe drought. The buffalo consumed all of the mix and retained their BCS of 3, whereas the cattle consumed between 200-300g/day of the mix and their BCS declined from 1.5 to 1.0 during the trial. Analysis of data points (buffalo n=309; cattle n=378) found average methane concentration (AMP) per animal of both cohorts increased over the 2 week baseline period, then declined during the supplementation period by 36% in the buffalo and 18% in cattle cohorts.

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

Lead-acid batteries utilised in electrical substations release hydrogen and oxygen when these are charged. These gases could be dangerous and cause a risk of fire if they are not properly ventilated. Therefore, this research seeks to design and implement a network control panel for heating, ventilation, and air-conditioning systems (HVACS). This is done using a specific range of controllers, which have more than thirty loops of proportional, integral and derivative (PID) control to achieve a cost-effective design. It performs the required function of extracting hydrogen, oxygen, and maintaining the desired temperature of the battery storage room within the recommended limits (i.e. 25°C ±1°C tolerance) without compromising quality as set out in the user requirement specification in Appendix-A. The system control panel allows the user to access control parameters such as changing temperature set-points, fan-speed, sensor database amongst others. The hardware is configured to detect extreme hydrogen and oxygen gas content in the battery room and ensure that the HVACS extract the gas content to the outside environment. The results of the system show that the network control panel effectively operates as per the recommended system requirements. Therefore, the effective operation of the HVACS ensures sufficient gas ventilation, thus mitigating the risk of fire in a typical battery storage room. Furthermore, the effective operation of HVACS enhances battery lifespan because of regulated operating temperature, which is conducive to minimise the effect of sulfation in lead acid Batteries (LABs).

The acquisition of adverbs in French as L2 (FSL) by learners with different L1s, at various levels of proficiency, has been extensively studied within various SLA projects (ESF, Interfra etc.). In the generativist tradition, it has been noted that “high category adverbs” such as those related to Mood-evaluative, Mood-epistemic and Tense are present early in FSL data. In the functionalist school, the early presence of time adverbs and scope particles in learner varieties has been analysed in relation with the informational and syntactic structures observed in these varieties and in terms of their contribution to temporal reference and other semantic domains in discourse.

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

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

The phytoplankton community in 66 reservoirs ubicated at the hydrographic basin of the Ebro River (Spain) was analyzed. Samples were collected in the summer season during the period 2010-2015, with the main purpose of evaluate the Trophic State and Ecological Potential according to the Water Framework Directive of the European Union. In this work we presented a representative overview of several consecutive years of the state of the reservoirs and their associated trophic status; methodology was to obtain statistically significant relationships between the phytoplankton community and main physicochemical water quality variables (water transparency, pH, chlorophyll a, total and soluble phosphorus, anoxic zone depth, nitrite, nitrate and ammonium concentrations). We provide data for retrospective comparative of the state of the reservoirs with previous and current studies in order to improve the management of these reservoirs, and to serve as data reference for future works in a context of global change (climate and pollution).

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

This study presents the first genome assembly of the freshwater saprobe fungus Neonectria lugdunensis and a comprehensive phylogenomics analysis of the Nectriaceae family, examining genomic traits according to fungal lifestyles. The Nectriaceae family, one of the largest in Hypocreales, includes fungi with significant ecological roles and economic importance as plant pathogens, endophytes, and saprobes. The phylogenomics analysis identified 2684 single-copy orthologs, providing a robust evolutionary framework for the Nectriaceae family. We analyzed the genomic characteristics of 17 Nectriaceae genomes, focusing on their carbohydrate-active enzymes (CAZymes), biosynthetic gene clusters (BGCs), and adaptations to environmental temperatures. Our results highlight the adaptation mechanisms of N. lugdunensis, emphasizing its capabilities for plant-litter degradation and enzyme activity in varying temperatures. Comparative genomics of different Nectriaceae lifestyles revealed significant differences in genome size, gene content, repetitive elements, and secondary metabolite production. Endophytes exhibited larger genomes, more effector proteins, and BGCs, while plant pathogens had higher thermo-adapted protein counts, suggesting greater resilience to global warming. In contrast, the freshwater saprobe shows less adaptation to warmer temperatures and is important for conservation goals. This study underscores the importance of understanding fungal genomic adaptations to predict ecosystem impacts and conservation targets in the face of climate change.

The microstructure of the substrate plays a crucial role in the anodizing process. Anodizing cast aluminum alloys is quite challenging due to the higher levels of alloying elements present compared to pure aluminum. Elements such as silicon, iron, and copper significantly impact the growth and quality of the anodic layer. Additionally, anodizing parameters such as electrolyte composition, current density, and temperature are critical in determining the morphology and thickness of the anodic film. The casting process, surface condition, and post-treatment also affect the properties of the anodic layer. Optimizing these parameters is essential to achieve a durable and high-quality anodic layer. This work aims to provide a comprehensive understanding of the various factors affecting the anodizing of cast aluminum alloys and the properties of the anodic layer, including its thickness, corrosion resistance, and wear resistance.

Noise in requirements has been known to be a defect in software requirements specifications (SRS). Detecting defects at an early stage is crucial in the process of software development. Noise can be in the form of irrelevant requirements that are included within a SRS. A previous study had attempted to detect noise in SRS, in which noise was considered as an outlier. However, the resulting method only demonstrated a moderate reliability due to the overshadowing of unique actor words by unique action words in the topic-word distribution. In this study, we propose a framework to identify irrelevant requirements based on the MultiPhiLDA method. The proposed framework distinguishes the topic-word distribution of actor words and action words as two separate topic-word distributions with two multinomial probability functions. Weights are used to maintain a proportional contribution of actor and action words. We also explore the use of two outlier detection methods, namely Percentile-based Outlier Detection (PBOD) and Angle-based Outlier Detection (ABOD), to distinguish irrelevant requirements from relevant requirements. The experimental results show that the proposed framework was able to exhibit better performance than previous methods. Furthermore, the use of the combination of ABOD as the outlier detection method and topic coherence as the estimation approach to determine the optimal number of topics and iterations in the proposed framework outperformed the other combinations and obtained sensitivity, specificity, F1-score, and G-mean values of 0.59, 0.65, 0.62, and 0.62, respectively.

Obesity has increasingly become a worldwide epidemic, as demonstrated by epidemiological and clinical studies. Obesity may lead to development of a broad spectrum of cardiovascular diseases (CVDs), such as coronary heart disease (CHD), hypertension, heart failure (HF), cerebrovascular disease, atrial fibrillation (AF), ventricular arrhythmias, and sudden cardiac death (SCD). In addition to hypertension, there are other cardiometabolic risk factors (CRFs) such as visceral adiposity, dyslipidemia, insulin resistance, diabetes, elevated levels of fibrinogen, and C-reactive protein and others, all of which increase the risk of CVD events. Mechanisms involved between obesity and CVD mainly include insulin resistance, oxidative stress, inflammation, and adipokines dysregulation, which cause maladaptive structural and functional alterations of the heart, particularly left ventricular (LV) remodeling and diastolic dysfunction. Natural products of plants, provide a diversity of nutrients and different bioactive compounds, including phenolics, flavonoids, terpenoids, carotenoids, anthocyanins, vitamins, minerals, fibers, and others, which possess a wide range of biological activities including antihypertensive, antilipidemic, antidiabetic, and other activities, thus conferring cardiometabolic benefits. In this review, we discussed the main therapeutic interventions using extracts from herbs and plants in preclinical and clinical trials with protective properties targeting CRFs. Molecular mechanisms and therapeutic targets of herbs and plants extracts for the prevention and treatment of CRFs are also reviewed.

With the increasing availability of large digitized fine art collections, automated analysis and classification of paintings is becoming an interesting area of research. However, due to domain specificity, implicit subjectivity, and pervasive nuances that vaguely separate art movements, analyzing art using machine learning techniques poses significant challenges. Residual networks, or variants thereof, are one the most popular tools for image classification tasks, which can extract relevant features for well-defined classes. In this case study, we focus on the classification of a selected painting 'Portrait of the Painter Charles Bruni' by Johann Kupetzky and the analysis of the performance of the proposed classifier. We show that the features extracted during residual network training can be useful for image retrieval within search systems in online art collections.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

In the context of global warming and increasing scarcity of fresh water resources, it becomes significant to evaluate the contribution and evolution of non-rainfall waters such as dew. This study therefore aims to evaluate the relative dew and rain contributions in three sites of south-western of Madagascar (Ifaty, Toliara and Andremba), a semi-arid region which suffers from a strong water deficit. The studied period is 1/1991 – 7/2023, with extrapolation to 8/2033. Dew is calculated from meteo data by using a well-established energy model. The extrapolation of dew and rain follows an artificial neural network approach. It is found that dew forms regularly (2-3 days in average between events), in contrast to rain (10-15 days). The evolutions of dew and rain are similar, with an increase from 1991 to 2000, a decrease up to 2020 and a further increase until 2033. These oscillations follow the Indian Ocean dipole variations and should be influenced by the climate change. Dew contribution to the water balance remains modest on a yearly basis (3-4%) but is important during the dry season (Apr.-Oct.), up to 30%. Dew therefore appears to be a reliable and sustainable resource for plants, small animals and population, especially during droughts.

Motivated by South Africa's need in the transition to a net-zero economy; this study 10 investigates the integration of renewable energy sources (RES) into oil refineries, considering 11 therein unique challenges and opportunities. The research focuses on optimizing RES allocation 12 using Particle Swarm Optimization (PSO), a data-driven approach that adapts to real-time 13 operational conditions. Traditional energy management systems often struggle with the inherent 14variability of RES, leading to suboptimal energy distribution and increased emissions. Therefore, 15 this study proposes a PSO-based renewable energy allocation strategy specifically designed for oil 16 refineries. It considers factors like the levelized cost of energy, geographical location, and available 17 technology. The methodology involves formulating the optimization problem, developing a PSO 18 model, and implementing it in a simulated oil refinery environment. The results demonstrate 19 significant convergence of the PSO algorithm, leading to an optimal configuration for integrating 20 RES and achieving cost reductions and sustainability goals. The optimization result of 4,457,527.00 21 Rand achieved by iterations is much better than the result of 4,829,638.88 Rand acquired using 22Linear Programming as the baseline model. The mean cost, indicating consistent performance, has 23 remained at its original value of 4,457,527.00 Rand, highlighting the convergence. Key findings 24 include the average distance measure decreasing from 4.2 to 3.4, indicating particle convergence; 25 swarm diameter decreasing from 4.7 to 3.8, showing swarm concentration on promising solutions; 26 average velocity decreasing from 7.8 to 4.25, demonstrating refined particle movement; and the 27 optimum cost function achieved at 4,457,527 Rand with zero standard deviation, highlighting 28 stability and optimal solution identification. This research offers a valuable solution for oil 29 refineries seeking to integrate RES effectively, contributing to South Africa's transition to a 30sustainable energy future.

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

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

There are currently worldwide efforts to reduce sugar intake due to the various adverse health effects linked with the overconsumption of sugars. Artificial sweeteners have been used as an alternative to nutritive sugars in numerous applications; however, their long-term effects on human health remain controversial. This led to a shift in consumer preference towards non-caloric sweeteners from natural sources. Thaumatins are a class of intensely sweet proteins found in arils of the fruits of the West-African plant Thaumatococcus danielli. Thaumatins’ current production method through aqueous extraction from this plant and uncertainty of the harvest from tropical rainforests limits its supply while the demand is increasing. Despite successful recombinant expression of the protein in several organisms, no large-scale bioproduction facilities exist. We present preliminary process design, process simulation, and economic analysis for a large-scale (50 metric tons/year) production of thaumatin II variant by several different molecular farming platforms.

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

This academic paper explores the synergistic potential of Agroforestry systems and Climate-Smart Agriculture (CSA) in enhancing climate change adaptation strategies. Focusing on Australia and Pacific Island Countries, the study delves into the pivotal role of these approaches in mitigating the impacts of changing climate variables on agricultural production. By analysing important climate variables, their potential alterations, and their subsequent effects on crop production, the paper advocates for a holistic and forward-thinking approach to sustainable agriculture in the face of climate change.

This article presents a buck converter in which the inductor has been replaced by a transmission line. This approach would be practically conceivable if the power supply and load have a greater spatial distance. In the time domain, this new converter can be described by a system of coupled partial and ordinary differential equations. In the frequency domain, a transcendental transfer function is obtained. For comparison with an equivalently parameterized conventional converter, Padé approximants are derived. A linear controller is designed for the converter topology under consideration.

Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for windspeed. Mean CVs were about 25% greater over ocean than over land, and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the wind and solar resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given persistence or predictability of climate modes with which these fluctuations are associated.

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

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

Ras is the most frequently mutated oncogene and recent drug development efforts have spurred significant new research interest. Here we will review progress toward understanding how Ras functions in nanoscale, proteo-lipid signaling complexes on the plasma membrane, called nanocluster. We will discuss how G-domain reorientation is plausibly linked to Ras-nanoclustering and -dimerization. We will then look at how these mechanistic features could cooperate in the engagement and activation of RAF by Ras. Moreover, we will show how this structural information can be integrated with microscopy data that provide nanoscale resolution in cell biological experiments. Synthesizing the available data, we propose to distinguish between two types of Ras nanoclusters, an active, immobile RAF-dependent type and an inactive/ neutral membrane anchor-dependent. We conclude that it is possible that Ras reorientation enables dynamic Ras dimerization, while the whole Ras/ RAF complex transits into an active state. These transient di/oligomer interfaces of Ras may be amenable to pharmacological intervention. We close by highlighting a number of open questions including, whether all effectors form active nanoclusters and whether there is an isoform specific composition of Ras nanocluster.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

Calotriton arnoldi is an endemic amphibian inhabiting Montseny Natural Park and Biosphere Re-serve (PNRBM). It was recognized as a new taxon in 2005 by means of genetic and morphologi-cal analyses and, due to its small distribution range and population size, it was listed as “Criti-cally endangered (CR)” by IUCN. Its area of distribution is small and fragmented less than line-ar 5 km. The Montseny Brook Newt is adapted to mountain streams and requires a pristine hab-itat, one which is currently being affected by conservation issues linked to climate change and human activities (logging, water catchments, visitor’s frequency, among others). At the end of 2016, the Life Tritó del Montseny (LifeTM) project (LIFE15 NAT/ES/000757) was launched. This project’s aim was to promote around fifty actions to ensure the conservation of C. arnoldi and its natural habitat, in the Montseny SCI of the Natura 2000 Network, with five strategic lines: 1) To increase scientific and technical knowledge with regard to C. arnoldi conservation status and its habitat management. 2) To ensure its genetic conservation and expand its geographic distribu-tion 3) To eliminate or minimize threats that exist in the riparian habitat. 4) To Involve and en-gage stakeholders and local residents in the conservation of Montseny brook newt riparian hab-itats. 5) To establish proper legal coverage and define long-term strategic planning. Since 2017, several actions linked to the strategic lines 1 and 3 have been initiated. Many unforeseen events have been overcome and there have been some failures, but there have also been several satis-factory results that allow us to be optimistic about the future of the species. These achievements and failures obtained throughout the process provide us with essential information to develop an adaptive habitat management. Dozens of monitoring surveys have been carried out which allow us to understand the evolution of natural populations, to improve our knowledge re-garding their biology and to assess the impact of conservation actions. In relation to eliminating or minimizing threats to the newt’s habitat, some of the actions that are being carried out are: a) Land acquisitions and land exchanges with different private properties. b) Land stewardship with two custody agreements being signed. c) Reduction of water withdrawal with nine water catchments and distribution being remodeled. e) Improvement of water treatments and storage by installing ecological wastewater treatment facilities. f) Ensure ecological connectivity and ri-parian forest restoration by removing twenty-two river connectivity barriers removed and exe-cuting twelve forestry and bioengineering interventions within the riverside habitat. With re-gard to analyzing the conservation status, management activities and scientific and technical knowledge, active long-term monitoring of the newt population and hydrological conditions has begun. Here we present an evaluation of the actions carried out to improve the habitat of this species, including the necessary considerations for them to be implemented correctly and to be successful in a natural area, which is under public-private management.

Although RNA modifications were discovered decades ago, the identification of enzymes that write, read, and erase RNA modifications enabled their functional study and spawned the field of epitranscriptomics. Coupling that knowledge to new methods has enabled the precise pinpointing of epitranscriptomic modifications across the transcriptome plus the elucidation of their functional consequences. PCIF1 (Phosphorylated CTD Interacting Factor 1) was shown to add N6, 2’-O-dimethyladenosine (m⁶Am) marks at the first nucleotide after the 5’ N7-methylguanosine (m⁷G) cap. In this review, we discuss the epitranscriptomic regulation of mRNA in general, and focus on m⁷G cap-adjacent m⁶Am in particular. m⁶Am positions can now be distinguished from N6-methyladenosine (m⁶A) using new techniques leveraging PCIF1-knockout cells. Although m⁶Am modification sites can be detected precisely, conflicting data have been published regarding how cap-adjacent m⁶Am marks affect their host mRNA. Discrepancies in the data mean that the effects of cap-adjacent m⁶Am on mRNA stability, decapping, and translation continue to be debated. Finally, while PCIF1 is predominantly nuclear, a subset of results suggest a possible cytoplasmic role as well. Taken together, these contradictory results which employed different methodologies and cell lines means that further experiments are required to determine the ultimate biological function(s) of m⁷G cap-adjacent m⁶Am.

This study is centred on Insecurity and Electoral Administration in Nigeria. Elections are the leading mechanism for selecting governments and a cardinal feature of democratisation. The quest for fair representation, development, good governance, inclusiveness and a true sense of belonging has been the driving force for election. The conduct of credible elections remains one of the thorny and fundamental issues in a democracy. The trajectory of electoral administration in Nigeria is long and tortuous; it precedes independence and is punctuated by the elite's scheming and cunning, electoral fraud, gimmicks and violence. Nigeria has had its fair share of insecurity from diverse sources such as banditry, insurgency, recurring violent religious crises, ethnic, resource and poverty-induced militancy, and crises occasioned by the clamour for self-determination. This has left the electoral management body in a quandary and has undoubtedly imperilled the administration of elections in Nigeria and equally accentuated the temerity for a holistic approach in reversing the trend and engendering the right atmosphere for the administration of elections. This study depends mainly on secondary sources and uses qualitative means in data analysis. It is revealed in this study that violence and various degrees of interruptions have taken the front burner in the democratisation process and are one of the dangerous dimensions in electoral administration; electoral politics remains one of the remarkable principal bases of clashes, political failure and social dislocation, Elections and their administration are some of the most complicated, time-sensitive activities undertaken by any country which will be exacerbated by insecurity. Democratic elections are successful when the electorate can make informed decisions; when faith in the process is sustained; when fraud is disincentivised, detected and punished. When insecurity is whittled down, mitigated or eradicated. The need for electoral security can never be overemphasised.

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

In the last decades we have experienced great social, cultural, and educational changes, spending more time performing tasks in near vision and less hours in outdoor activities, having more overexposure to digital screens, especially the youngest and increasingly from younger ages. It is common to see cases when performing tasks in near vision the posture or position of the head is not adequate, especially the youngest, being essential to have a correct posture of the head to avoid visual, muscular, or articular problems. We present a procedure to try to control the correct position of the head in real time when performing close-up activities. The aim is to detect the inclination of the head and to know if a bad position is adopted due to a visual problem or simply to inadequate visio-postural habits, warning us of the postural anomaly to correct it.

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

The aims of study was to evaluate the effects of rates, sources and timing of nitrogen application under cover of transgenic corn yield cultivated in Amazon Biome. The experiments were conducted in Parauapebas city, State of Pará, Brazil, in two years (2016/2017 and 2017/2018). The experimental design was randomized blocks, in a 5x2x2 factorial scheme, consisting of five rates of N (0; 45; 90; 135; and 180 kg ha-1), two nitrogen sources (urea and ammonium sulfate) and two application times of N (phenological stages V4 and V8), with four replications. The factor N rates promoted adjustment of linear equation (leaf area index, mass of thousand grains, and yield) and quadratic equation (dry mass of leaf index). Nitrogen fertilization promoted significant increases in mass of thousand grains and yield, obtaining the best results with 180 kg ha-1 of N applied at V4 phenological stage. Based on results obtained in two years of corn cultivated under conditions of Amazon Biome, the application of N at V4 phenological stage at rates of 121 to 131.39 kg ha-1 of N showed the best results for vegetative growth, while 180 kg ha-1 of N, regardless of source used, urea or ammonium sulfate, promoted greater grain weight and greater yield.

A paradigm shift away from null hypothesis significance testing seems in progress. Based on simulations, we illustrate some of the underlying motivations. First, P-values vary strongly from study to study, hence dichotomous inference using significance thresholds is usually unjustified. Second, statistically significant results have overestimated effect sizes, a bias declining with increasing statistical power. Third, statistically non-significant results have underestimated effect sizes, and this bias gets stronger with higher statistical power. Fourth, the tested statistical hypotheses usually lack biological justification and are often uninformative. Despite these problems, a screen of 48 papers from the 2020 volume of the Journal of Evolutionary Biology exemplifies that significance testing is still used almost universally in evolutionary biology. All screened studies tested default null hypotheses of zero effect with the default significance threshold of p = 0.05, none presented a pre-specified alternative hypothesis, pre-study power calculation, and the probability of ‘false negatives’(beta error). The results sections of the papers presented 49 significance tests on average (median 23, range 0–390). Of 41 studies that contained verbal descriptions of a ‘statistically non-significant’ result, 26 (63%) falsely claimed the absence of an effect. We conclude that studies in ecology and evolutionary biology are mostly exploratory and descriptive. We should thus shift from claiming to ‘test’ specific hypotheses statistically to describing and discussing many hypotheses (possible true effect sizes) that are most compatible with our data, given our statistical model. We already have the means for doing so, because we routinely present compatibility (‘confidence’) intervals covering these hypotheses.

Nowadays, all the stakeholders, policy makers, regulators, aircraft designers, producers, operators, etc.) are intensively working on development of the aircraft with full electric and hybrid propulsion systems. However, the technical, technological constrains (like limit on accumulator energy density) require introducing a new approach to conceptual design of such aircraft. The new methods is based on energy and mass balance evaluation. This paper analyses the identified constrains; integrates the energy and mass balance equations into the preliminary definition and calculations of the aircraft performance. By this way, the technological constrains might be transferred into the limitation on the aircraft energy and mass breakdown, that initiates a new approach to aircraft conceptual design uses the knowledge based multidisciplinary optimization. The paper describes the developed methodology for conceptual design of aircraft. It show results of implementing this new development philosophy to conceptual design of a four-seat small electric/hybrid aircraft and a special hybrid cargo UAV. The discussion of the results including got by using the emerging and enabling new technologies and new methods and solutions (including for example distributed propulsion system, unconventional forms, morphing, biomimics, etc.), demonstrates the possible implementation of the new development philosophy, new approach to aircraft conceptual design.

Background: Our previous study highlighted important healthcare access and utilization concerns among new immigrants. Hence, in this study, we aimed to explore the role of public and patient involvement (PPI) may have in enhancing the accessibility and their contribution to migration health studies. Method: An open and in-depth interactive consecutive virtual discussion was conducted among volunteer asylum seekers and refugees from Eritrea and Syria in Switzerland. The novel PPI establishment had three phases; inception, training phase, and contribution phase. Result: At the beginning, the concept of PPI was apprehensive to grasp, as it was a new approach. After training and consecutive discussions, volunteers were ardent to engage actively. Hence, among the prime findings were the PPI's role and effect in raising awareness, PPI's role in exploring and communicating the healthcare system accessibilities and utilization among their community, the impact of PPI in echoing the healthcare needs of their fellow migrants, and PPI's contribution in enhancing and strengthening migration health researches. Conclusion: The PPI volunteers in the study were keen to raise their community's awareness through their networks, and bridge the research gap between researchers and the public.

The Planning and implementation of construction projects are difficult processes and are burdened with many risk elements. The budget spread over time, which is developed on the basis of the schedule, presents the expected distribution of costs throughout the duration of the works, which during the implementation of the project is subject to constant changes resulting from time, cost and organizational factors. Managing construction contracts requires managers to be able to analyze on an ongoing basis the variances of production costs - from the values calculated in the offer cost estimate and assumed in the Budgeted Cost of Work Scheduled. The article attempts to analyze the emerging time and cost deviations using proprietary T/S and T/C monitoring, based on simple indicators of the EVM method. An example of construction of a multi-family housing development was used to study the variances of planned and incurred costs.

We propose a probabilistic graphical model for discriminative substrate characterization, to support geological and biological habitat mapping in aquatic environments. The model, called a fully connected conditional random field (CRF), is demonstrated using multispectral and monospectral acoustic backscatter from heterogeneous seafloors in Patricia Bay, British Columbia, and Bedford Basin, Nova Scotia. Unlike previously proposed discriminative machine learning algorithms, the CRF model considers both the relative backscatter magnitudes of different substrates and their relative proximities. The model therefore combines the statistical flexibility of a machine learning algorithm with an inherently spatial treatment of the substrate. The CRF model predicts substrates such that nearby locations with similar backscattering characteristics are likely to be in the same substrate class. The degree of proximity and allowable backscatter similarity are controlled by parameters that are learned from the data. CRF model results were evaluated against a popular generative model known as a Gaussian Mixture model that doesn't include spatial dependencies, only covariance between substrate backscattering response over different frequencies. Both models are used in conjunction with sparse bed observations/samples in a supervised classification. A detailed accuracy assessment, including a leave-one-out cross-validation analysis, was performed using both models. Using multispectral backscatter, the GMM model trained on 50% of the bed observations resulted in a 75% and 89% average accuracies in Patricia Bay and Bedford Basin, respectively. The same metrics for the CRF model were 78% and 95%. Further, the CRF model resulted in a 91% mean cross-validation accuracy across four substrate classes at Patricia Bay, and a 99.5% mean accuracy across three substrate classes at Bedford Basin, which suggest that the CRF model generalizes extremely well to new data. This analysis also showed that the CRF model was much less sensitive to the specific number and locations of bed observations than the generative model, owing to its ability to incorporate spatial autocorrelation in substrates. The CRF approach therefore may prove to be a powerful `spatially aware' alternative to other discriminative classifiers.

This review focuses on the synthesis and biological activity of flavones and their related flavonoidic compounds: flavonols and aurones. Among the biological activities of flavones and aurones, the anticancer, antioxidant and antimicrobial properties are highlighted and detailed in this review. The most applied method for the synthesis of flavones and aurones is based on the oxidative cyclisation of o-hydroxychalcones. Depending on the reaction conditions and the structure of the precursor, in some cases several cyclization products result simultaneously: flavones, flavanones, flavonols and aurones. Based on the literature data and the results obtained in our research group, our aim is to highlight the most promising methods for the synthesis of flavones, as well as the synthetic routes for the other structurally related cyclization products, hydroxyflavones and aurones, considering that in practice it is difficult to predict which is the main or exclusive cyclisation product of o-hydroxychalcones under certain reaction conditions.