Latin America and the Caribbean offer the most favorable natural and social conditions for the emergence of cattle ranching that regenerate and maintains the ecosystem services on which life on Earth depends, that is energy efficient and that contributes to meeting fundamental human food needs. Unlike other major global producers, cattle farming in Latin America and the Caribbean is fundamentally based on pasture. Therein lies both its strength (due to the regenerative potential of well-managed pastures) and its vulnerability (due to the pervasive link between deforestation and pasture formation, especially in the Amazon, where 40% of the Brazilian herd is concentrated). The diversification of pastures (today marked by impressive monotony, with brachiaria accounting for 85% of the species in Brazil), the introduction of legumes and tree plantations within them, and the proper management of herds, open the way to the possibility of drastically reducing the area currently occupied by the activity (especially in the Amazon) while maintaining the supply of its products. Agricultural research has disseminated forms of moderate intensification of cattle ranching, which represent a low opportunity cost of animal feed and, at the same time, regeneration of ecosystem services that have so far been destroyed by the prevailing methods of farming.

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

This article presents a combined route and path planning strategy to guide Skid-Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity, and ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrated the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

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

Whilst prior works have characterised the affordances of prototyping methods in terms of generating knowledge about a product or process, the types, or ‘dimensions’ of knowledge towards which they contribute are not fully understood. In this paper we adapt the concept of ‘design domains’ as a method to interpret, and better understand the contributions of different prototyping methods to design knowledge in new product development. We first synthesise a set of ten dimensions for design knowledge from a review of literature in design-related fields. A study was then conducted in which participants from engineering backgrounds completed a Likert-type questionnaire to quantify the perceived contributions to design knowledge of 90 common prototyping methods against each dimension. We statistically analyse results to identify patterns in the knowledge contributions of different methods. Results reveal that methods exhibit significantly different contribution profiles, suggesting different methods to be suited to different knowledge generation. Thus, this paper indicates potential for new methods, methodology and processes to leverage such characterisations for better selection and sequencing of methods in the prototyping process.

Metallic masters can be used as a metallic mold to replicate polymeric pieces with high resolution. Metallic masters with high resolution were created by photolithography technique and nickel electrodeposition technique. AZ 9260 photoresists and SPR 220-7.0 photoresists were used to coat metallic substrates and to compare results. Steel substrate and nickel substrate were used as the metallic substrate to compare results. Two different nickel electrodeposition protocols were used to compare results. In the conclusion section, was determined the best photoresist, metallic substrate, and nickel electrodeposition protocol to fabricate metallic masters.

The Covid-19 pandemic has resulted in the closure of schools at every level, globally, forcing education to move online. Meeting the needs of students online for Science Lab classes, in particular, is a challenge since the physical labs are not available to the teachers or students. OLabs is a virtual Science Lab providing a complete learning environment of theory, experimental procedures, videos, animations, simulations, and assessments that capture real lab experiences with the relevant pedagogy. This study looks at the acquisition and behaviors of users, on the OLabs platform, during pre and Covid-19 times. Using Google Analytics, we observe that, during the pandemic time, users increasingly adopted OLabs as a new learning pedagogy for performing experiments as indicated by parameters like the number of users; the number of unique pages viewed per session; time spent on viewing content; bounce rate; and preference for content types such as theory, simulations, videos, and animations.

Background. Until now, cost of allergy treatment in insured public health care system and non-insured self-financing private health care system in Indonesia has not been well documented and published, as well as the cost of allergy treatment with subcutaneous immunotherapy. Objective. To evaluate the clinical and cost benefits of allergic rhinitis treatment in children with subcutaneous immunotherapy in non-insured self-financing private health care system. Methods. A retrospective cohort study conducted from 2015 until 2020, compared clinical improvement and health care costs over 18 months in newly diagnosed AR children who received SCIT versus matched AR control subjects who did not receive SCIT, with each group consisting of 1,098 subjects Results. Decrease of sp-HDM-IgE level (kU/ml) from 20.5 + 8.75 kU/ml to 12.1 + 3.07 kU/ml had been observed in the SCIT group. To reduce the symptom score of allergic rhinitis by 1.0 with SCIT it costs IDR 21,753,062.7 per child, for non SCIT it costs IDR 104,147,878.0 per child. Meanwhile, to reduce the medication score (MS) by 1.0 with SCIT it costs Rp. 17,024,138.8 while with non SCIT it costs Rp. 104,147,878.0. Meanwhile, to lower combination symptoms and medication score (CSMS) by 1.0, with SCIT it costs IDR 9,550,126.6, while with non SCIT it costs IDR 52,073,938.9. Conclusion. In conclusion, this first Indonesia-based study demonstrates substantial health care cost savings associated with SCIT for children with AR in an uninsured private health care system and provides strong evidence for the clinical benefits and cost-savings benefits of AR treatment in children.

This research work uses a simplified approach to combine location information from beacons propagation signal interaction with a mobile device with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user’s orientation inside unknown buildings and the data stored from different users can provide useful information about users movements inside a public building. Beacons installed on the building at specific pre-defined position emit signals that give a geographic position with an associated imprecision, related with Bluetooth’s range. This uncertainty is handled by building layout and users’ movement in a developed system that maps users’ position, gives guidance and store user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user ‘s smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively.

Water footprint has been widely used to illustrate the consumption of water in many situations; for instance, in products, processes or regions of interest. In this work, we analyzed – using a sensitivity analysis approach – the effect of some variables in the calculation of the water footprint in the viticulture in Brazilian Serra Gaúcha (the major producing region of Brazilian Wine).The classical Penman-Monteith model for evapotransporation was considered, with uncertainties in some parameters (dead mulch covering fraction in the vineyard, maximum temperatures for some months, altitudes and latitudes of the site). The sensitivity analysis was conducted using the SAFE toolbox under Octave framework. The results indicated that the the portion of the water footprint corresponding to the evapotranspiration is more sensitive to the values of mulch covering fraction and the altitude of the site in comparison with the latitude and the maximum temperatures.

We consider an $N$ fermion system at low temperature $T$ in which we encounter special particle number values $N_m$ exhibiting special traits. These values arise in focusing attention upon the degree of mixture (DM) of the pertinent quantum states. Given the coupling constant of the Hamiltonian, the DMs stay constant for all $N$-values, but experience sudden jumps at the $N_m$. For a quantum state described by the matrix $\rho$, its purity is expressed by $Tr \rho^2$ and then the degree of mixture is given by $1 - Tr \rho^2$, a quantity that coincides with the entropy $S_q$ for $q=2$. Thus, Tsallis entropy of index two faithfully represents the degree of mixing of a state, that is, it measures the extent to which the state departs from maximal purity . Macroscopic manifestations of the degree of mixing can be observed through various physical quantities. Our present study is closely related to properties of many-fermion systemsn that are usually manipulated at zero temperature. Here we wish to study the subject at finite temperature. Gibbs' ensemble is appealed to. Some interesting insights are thereby gained.

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consist of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to LNG terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

India is ranked 5th in world in terms of Covid-19 publications accounting for 6.7% of the total. About 60% of the Covid-19 publications in the year 2020 are from United States, China, UK, Italy, and India. We present a bibliometrics analysis of the publi-cation trends and citation structure along with identification of major research clusters. By performing network analysis of authors, citations, institutions, key-words, and countries, we explore semantic associations by applying visualization techniques. Our study shows lead taken by United States, China, UK, Italy, India in Covid-19 research may be attributed to the high prevalence of Covid-19 cases in those countries witnessing the first outbreak and also due to access to Covid-19 data, access to labs for experimental trials, immediate funding, and overall support from the govt. agencies. Large number of publications and citations from India are due to co-authored publications with countries like United States, UK, China, and Saudi Arabia. Findings show health sciences with highest the number of publications and citations, while physical sciences and social sciences and humanities counts were low. A large proportion of publications fall into the open access category. With India as focus, by comparing three major pandemics SARS, MERS, Covid-19 from biblio-metrics perspective, we observe much broader involvement of authors from multiple countries for Covid-19 studies as compared to SARS and MERS. Finally, by applying bibliometric indicators, we see an increasing number of sustainable develop-ment-related studies from the Covid-19 domain, particularly concerning the topic of good health and well-being. This study allows for a deeper understanding on how the scholarly community from a populous country like India pursued research in the midst of a major pandemic which resulted in closure of scientific institutions.

In this study, using information theory tools, we investigate the quantum degree of mixedness, particle number fluctuations, and temperature variations in the paradigmatic Lipkin model, focusing on the interplay between these factors in a system of many fermions. Our analysis reveals intriguing dependencies of quantum mixedness on the total fermion number, showcasing distinct behaviors at different temperatures. Notably, we find that the degree of quantum mixedness exhibits a strong dependence on the total fermion number, with varying trends observed across different temperature regimes. Remarkably, this dependence remains unaffected by the strength of the fermion-fermion interaction (if it does not vanish, of course), underscoring the robustness of the observed phenomena. Through comprehensive numerical simulations, we provide illustrative graphs that depict these dependencies, offering valuable insights into the fundamental characteristics of many-fermion systems. Our findings shed light on the intricate dynamics of quantum degree of mixedness and particle number fluctuations in fermionic systems, with potential implications for diverse fields ranging from condensed matter physics to quantum information science.

In recent years, the advances in sperm morphology and genetic analyses in Perumytilus purpuratus allowed to suggest two evolutionary scenarios for this mussel: 1) the scenario of cryptic species and 2) the scenario of incipient or in progress speciation. To a better understanding of the evolutionary history of P. purpuratus, we performed an extensive sampling effort along a latitudinal gradient of ca. 7,180 km of coastline, from Southern Pacific to Atlantic Oceans and, we have also gone deeper in sperm morphology in P. purpuratus, exploring its association with phylogeny and population genetics to contrast if variability in sperm traits between northern and southern regions are signals of cryptic or incipient species. Overall, our results showed three sperm morphotypes and genetic structure in males of P. purpuratus strongly correlated. Additionally, we found evidence of a genetic admixture between lineages suggesting an introgressive hybridization zone at 38°S. These findings suggest the hypothesis that P. purpuratus is under incomplete reproductive isolation, with the presence of mechanisms of postzygotic isolation between lineages and, therefore, under an incipient or in fraganti speciation process. Finally, we discovered a new long morphotype for this species restricted to southern localities. Overall, our results support the hypothesis of historical events and postglacial recolonization as causal phenomena for the observed divergences.

This paper introduces a theory for the evolution of corporates in which the growth and sustainability strategies are developed simultaneously. Since the introduction of corporate sustainability, it has been an extra cost for risk mitigation and making ‘compensating’ positive impact. The world has reached a tipping point of volatility, mainly due to climate change but also by emergence of COVID-19, so that the applicability of existing corporate structures is under question and these poses high risk to the existence of our planet. On the other hand, the technology cost for sustainable investment has reached a parity in comparison with non-sustainable alternatives. Therefore, our proposed Organic Grow Theory introduces a step-by-step approach so that corporates can grow and be profitable without compromising the ability of future generations to meet their needs. It is concluded that, a new structure for corporate, called Founcorp, would be needed to direct corporates to evolve being a responsible legal entity.

In this research, the photocatalytic degradation of cypermethrin using Fe-TiO2 nanoparticles supported in a biomaterial was evaluated. The nanoparticles of TiO2 were synthesized by the green chemistry method assisted by ultrasound and doped by chemical impregnation using molar ratios Fe:Ti of 0, 0.05, 0.075 and 0.1, to make efficient use of direct sunlight (λ>310 nm). All nanoparticles were immobilized on the surface of spathe of coconut palm (Cocos nucifera). The degradation was carried out at room temperature and natural pH in a flat plate solar reactor, on which the composite material was subjected. The concentration of cypermethrin was determined after 12000 J/m2 of accumulated radiation from GC-MS and the resulting material was characterized by Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) image and selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), UV-Vis spectrophotometry of diffuse reflectance and BET surface area BET surface area. The best results were achieved with the use of Degussa TiO2 P-25, Fe:Ti=0 and Fe:Ti=0.05 in suspension, with percentages of degradation of cypermethrin of 99.84, 99.62, and 100%, respectively. However, the materials supported on the biomaterial of coconut, they allowed to reach degradation percentages higher than 80% with the advantage that it minimizes operating costs, since they are not necessary filtering or centrifuging processes to separate the catalyst.

Augmented and Virtual Reality have been experiencing a rapidly growth in recent years, but there is not still a deep knowledge on their capabilities and where they could be explored. In that sense, this paper presents a study on the accuracy and repeatability of the Microsoft's HoloLens 2 (Augmented Reality device) and HTC Vive (Virtual Reality device) using an OptiTrack system as ground truth. For the HoloLens 2, the method used was hand tracking, while in HTC Vive, the object tracked was the system's hand controller. A series of tests in different scenarios and situations were performed to explore what could influence the measures. The HTC Vive obtained results in the millimetre scale, while the HoloLens 2 revealed not so accurate measures (around 2 centimetres). Although the difference can seem to be considerable, the fact that HoloLens 2 was tracking the user's hand and not an inherit controller made a huge impact. The results were considered a significant step for the on going project of developing a human-robot interface to program by demonstration an industrial robot using Extended Reality, which shows great potential to succeed based on this data.

The augmenting commitment in the entrepreneurial learning process, both at academic and industry level, has led to new mechanisms and methodologies. Entrepreneurship literature has shown evidence of raising interest in the problem-based learning (PBL) methodology with regard to upcoming events from the surrounding learning context. This paper presents a Systematic Bibliographic Literature Review (SBLR) with respect to the application of PBL throughout distinct entrepreneurial processes either in higher education, or in industry. It aimed to identify relevant entrepreneurial opportunities for PBL. Bibliographic databases were searched for documents published between 2002 and May 2024 to categorize key topics discussed in the literature on PBL and entrepreneurship. The review process identified 142 empirical and non-empirical papers on entrepreneurship related PBL. Data analysis revealed diverse subthemes for PBL uses in entrepreneurship in both higher education institutions and industry. The research questions “What is the interplay of problem-based learning methodology with entrepreneurship?” guided the study. The central output of the research is the discovery of the varying uses of PBL to cope with diverse events arising within entrepreneurship context. Future research directions are suggested.

The importance of shifting to a sustainable economy, based on new capabilities that enable to cope with the current turbulent changes is paramount. Entrepreneurs with sustainable concerns are considered to play a key role in the process by creating innovative, proactive and risk assumption solutions, both with environmental and economic value. To date, there is no consensus on what capabilities education should provide to create sustainable entrepreneurs to cope with sustainability challenges. The aim of this piece of literature is to identify relevant factors for sustainable entrepreneurship education. Bibliographic databases were searched for documents published between 2012 and June 2023 to categorize central issues discussed in the literature on sustainable entrepreneurship education. The review process specifies 59 empirical and non-empirical papers at sustainable entrepreneurship education (SEE). Data analysis revealed diverse models for sustainable entrepreneurship education (SEE) developed for use in both higher education institutions and secondary schools. Future research directions are underscored.

The importance of transforming to a sustainable economy to protect against global crises such as climate change is widely recognized. Sustainable entrepreneurs are seen as playing a key role in this transformation process by creating innovative market solutions with environmental, social, and economic value. To date, there is no consensus on the skills education should deliver to create sustainable entrepreneurs to solve sustainability challenges. The goal of this article is to identify sustainable entrepreneurship education factors that enable effective education of future sustainable entrepreneurs. An academic search engine and bibliographic database were searched for documents written in English and published between 2012 and April 2023 to identify existing educational models discussed in the current literature in sustainable entrepreneurship education (SEE). The review process resulted in a set of 59 empirical and non-empirical papers on SEE. The data analysis revealed different educational frameworks for sustainable entrepreneurship (SE), both developed for use in higher education institutions and secondary schools.

Nowadays, people live amidst the smart home domain, business opportunities in the industrial smart city and health care, though, along with concerns about security. Security is central for IoT systems to protect sensitive data and infrastructure, whilst security issues become increasingly expensive, in particular in Industrial Internet of Things (IIoT) domains. Nonetheless, there are some key challenges for dealing with those security issues in IoT domains: Applications operate in distributed environments such as Blockchain, varied smart objects are used, and sensors are limited in what comes to machine resources. In this way, traditional security does not fit in IoT systems. In this vein, the issue of cyber security has become paramount to the Internet of Things (IoT) and Industrial Internet of Things (IIoT) in mitigating cyber security risk for organizations and end users. New cyber security technologies / applications present improvements for IoT security management. Nevertheless, there is a gap on the effectiveness of IoT cyber risk solutions. This review article discusses the, trends around opportunities and threats in cyber security for IIoT.

Diverse forms of artificial intelligence (AI in further text) are at the forefront of triggering digital security innovations, based on the threats that are arising in this post COVID world. On the one hand, companies are experiencing difficulty in dealing with security challenges with regard to a variety of issues ranging from system openness, decision making, quality control and web domain, just to mention a few. On the other hand, in the last decade, research has focused on security capabilities based on tools such as platform complacency, intelligent trees, modeling methods and outage management systems, in an effort to understanding the interplay between AI and those issues. The dependence on the emergence of AI in running industries and shaping the education, transports and health sectors is now well known in literature. AI is increasingly employed in managing data security across economic sectors. Thus, a literature review of AI and system secu-rity within the current digital society is opportune. This paper aims at identifying research trends in the field through a Systematic Bibliometric Literature Review (LRSB) of research on AI and system security. The review entails 77 articles published in Scopus® database, presenting up-to-date knowledge on the topic. The LRSB results were synthesized across current research subthemes. Findings are presented. The originality of the paper relies on its LRSB method, together with extant review of articles that have not been categorized so far. Implications for future re-search are suggested.

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

Since people spend most of their time in indoor environments, the objective of this work was to study indoor air quality perception and its effects on users’ thermal comfort. Based on previous data from a building with a central air-conditioning system and two mixed-mode buildings located in the humid subtropical climate of Florianópolis, southern Brazil, statistical analyses were performed. Each user subjective answer obtained through a questionnaire was combined with the corresponding environmental conditions – measured using microclimate stations, a portable thermo-anemometer and a CO2 analyser. Results showed that improvement in air quality was associated with the reduction of air temperature and humidity ratio. Also, there was a significant influence of thermal, air movement and humidity sensation and acceptability of air quality perception. Users felt more satisfied or neutral with air quality for being in thermal comfort, and not because of the CO2 level – which means that air quality perception is influenced by factors other than CO2. This study recommends the implementation of an air exchange device in split air-conditioners with air recirculation used in mixed-mode buildings in Brazil. It is important to provide suitable indoor ventilation to reduce pollutants concentration, ensure good air quality and prevent respiratory diseases.

The supply of mental health processes in primary care has gaps. This study aims to analyze the association of agreement criteria and flows between primary care teams and the Family Health Support Center (NASF) for mental health collaborative care, considering the difference between capital and non-capital cities in Brazil. This cross-sectional study was conducted based on secondary data from the Primary Care Access and Quality Improvement Program. Agreement criteria and flows were obtained from 3883 NASF teams of the matrix support or collaborative care. The Chi-square test and multiple Poisson regression were used; p < 0.05 was considered statistically significant. Prevalence ratios of negative associations demonstrated protective factors for support actions: follow-up at Psychosocial Care Center, management of psychopharmacotherapy, offer of other therapeutic actions, care process for users of psychoactive substances, and offer of activities to prevent the use of psychoactive substances. Collaborative care in primary care was effective, and capital cities were a protective factor compared with non-capital cities.

Strawberry is produced in tropical regions using imported cultivars adapted to temperate and subtropical climates. These cultivars, under tropical conditions, produce below their genetic potential. Through multivariate analyses, the objective was to evaluate and select short-day strawberry genotypes based on intraspecific crosses, product characteristics, and fruit quality. The genotypes were obtained from the cross between 'Camino Real' (female parent) and the first-generation genotypes RVCA16, RVCS44, RVFS06, RVFS07, and RVDA11 (male parent), obtained in previous selections. The experimental design consisted of augmented blocks with standard controls, consisting of first-generation genotypes and commercial cultivars. The fruits were harvested and evaluated for productivity and post-harvest characteristics: Total Fruit Mass (MTF); Total Number of Fruits (TFN); Average Fruit Mass (AFM); Commercial Fruit Mass (CFM); Fruit Commercial Number (CFN); Average Commercial Mass of Fruits (ACFM); Total Soluble Solids (TSS); Firmness (F); Brightness (L); Hue Angle (°Hue); Chroma (C). The selection index of Mulamba and Mock (1978) was used with an intensity of 3% to obtain superior genotypes and submitted to multivariate analysis for comparative purposes. Of the 1500 genotypes evaluated, it was possible to select 44 genotypes with characteristics superior to the 13 controls. The RVDA11CR59 genotype showed better values for the attributes of interest, but the RVCS44CR population, from the cross between 'Camino Real' × RVCS44 ('Camarosa' × 'Sweet Charlie'), obtained the highest number (16) of individuals among those selected. Significant traits had high heritability but were not necessarily reflected in high selection gain. Coefficients of genetic variation were high, indicating sufficient genetic variability to select genotypes for these traits. When multivariate analyses were used, it was possible to group the selected genotypes into the same cluster according to the similarity and balance in the responses to the evaluated variables, demonstrating that these analyses help other parameters choose superior genotypes. The multivariate analysis allowed the selection of more balanced genotypes for production and post-harvest traits for tropical climates.

Mechanical recycling of solid plastic wastes on a small-scale level can be accomplished with the correct approaches. Thermoplastics are mostly considered for mechanical recycling because of their physical properties and ease of reprocessing. This paper reviews the mechanical reprocessing techniques of selected thermoplastics (polyethylene terephthalate and polyolefins) since they constitute a significant proportion of plastics used commercially. Furthermore, necessary considerations for effective operation of small-scale plants, including energy requirements of machinery and optimisation in order to improve efficiency and product quality, are discussed. A clearer understanding and addressing of the process-related challenges will lead to successful establishment and management of small-scale mechanical recycling facilities to benefit communities. Efficient small-scale mechanical reprocessing establishments have become essential in reducing the environmental impacts of solid plastic wastes and for energy conservation.

In the field of embedded systems, energy efficiency is a critical requirement, particularly for battery-powered devices. RISC-V processors have gained popularity due to their flexibility and open-source nature, making them an attractive choice for embedded applications. However, not all RISC-V processors are equally energy-efficient, and it is important to evaluate their performance in specific use cases. This paper evaluates the energy consumption and resource utilization of a new RISC-V processor, RisCO2, and four existing processors - Zero-riscy, Micro-riscy, Ri5cy, and CV32E40P - in a signal demodulation application for NDIR CO2 sensors. The processors were implemented in the PULPino SoC and synthesized using Vivado IDE. The processor named RisCO2 is based on the RV32E_Zfinx instruction set and was designed from scratch by the authors specifically for low-power signal processing applications such as signal demodulation in CO2 NDIR sensors. The other processors are Ri5cy, Micro-riscy, and Zero-riscy, developed by the PULP Platform team, and CV32E40P (derived from Ri5cy) from the OpenHW Group, all of them widely used in the RISC-V community. Our experiments showed that RisCO2 had the lowest energy consumption among the five processors, with a 53.5% reduction in energy consumption compared to CV32E40P and a 94.8% reduction compared to Micro-riscy. Additionally, RisCO2 had the lowest FPGA resource utilization compared to the best-performing processors, CV32E40P and Ri5cy, with a 46.1% and a 59% reduction in LUTs, respectively. Our findings suggest that RisCO2 is a highly energy-efficient RISC-V processor for NDIR CO2 sensors that require signal demodulation. The results also highlight the importance of evaluating processors in specific use cases to identify the most energy-efficient option. This paper provides valuable insights for designers of energy-efficient embedded systems using RISC-V processors.

Aim: Child-to-parent offenders (CPOs) are commonly specialist offenders and with high rates of recidivism. Thus, a field study was designed to estimate the prevalence in the reference measures of recidivism i.e., dangerousness, risk factors and psychopathy, and compare CPOs with non-child-to-parent juvenile offenders. Method: 136 juvenile offenders (76.5% boys), 76 CPOs and 60 non-CPOs juvenile offenders, aged from 14 to 18 years old, were measured in dangerousness, risk of factors and psychopathic traits. Results: The results showed in CPOs a more than common prevalence (> .50), 75.0%, 95% CI [.653, .847], of dangerousness (caseness); a significant prevalence (> .05) of diagnostic of psychopathy, 25.0%, 95% CI [.150, .350]; and a common prevalence (= .50), 55.3%, 95% CI [.441, .665] of classification as high and very high risk by risk factors. Comparatively, no significant differences were observed between CPOs and non-CPOS juvenile offenders in mental health problems (dangerousness), meanwhile that CPOs exhibited significant more interpersonal and affective psychopathic traits and significant more risk in family circumstances, and personality and behaviour risk factors. Conclusions: The implications for prevention and intervention programs with CPOs are discussed

(1) Background: tuberculosis (TB) is considered one of the leading causes of death by a single in-fectious agent worldwide. This study aimed to identify hotspots of people diagnosed with tu-berculosis and abusive use of alcohol, tobacco and other drugs in communities through a geo-spatial intelligence application; (2) Methods: ecological study with a spatio-temporal approach. We considered tuberculosis cases diagnosed and registered in the Notifiable Diseases Information System, which presented information on alcoholism, smoking, and other drugs. Spatial Variations in Temporal Trends (SVTT) and scan statistics were applied for the identification of Hotspots; (3) Results: of 29.499 cases of tuberculosis were identified. And when we applied the STTT for al-coholism, three Hotspots were detected, one of which was protective (RR: 0.08 – CI95%: 0.02 – 0.32) and two at risk (RR:1.42 – CI95%: 1.11 – 1.73; RR: 1.39 - CI95%: 1.28 – 1.50). Regarding smoking, two risk clusters were identified (RR: 1.15 - CI95%: 1.01 – 1.30; RR: 1.68 - CI95%: 1.54 – 1.83). For other drugs, a risk cluster was found (RR: 1.13 - CI95%: 0.99 – 1.29) and two protections (RR: 0.70 - CI95%: 0.63 – 0.77; RR: 0.76 – CI95%: 0.65 – 0.89); (4) Conclusions: it was evidenced in the communities a problem of TB and drug addiction. Use disorder perhaps in a person's brain and behavior and leads to an inability to continue their treatment, putting the community at risk for TB.

This article introduces simulations of theoretical material with controlled properties for the evaluation of the effect of key parameters, as volumetric fractions, elastic properties of each phase and transition zone on the effective dynamic elastic modulus (Ed). The accuracy level of classical homogenization models was checked regarding the prediction of Ed. Numerical simulations were performed with finite element method (FEM) for evaluations of the natural frequencies and their correlation with Ed, through frequency equations. An acoustic test validated the numerical results and obtained the elastic modulus of concretes and mortars at 0.3, 0.5 and 0.7 water-cement ratios (w/c). Hirsch calibrated according to the numerical simulation (x = 0.27) exhibited a realistic behavior for concretes of w/c = 0.3 and 0.5, with 5% error. Nevertheless, for w/c = 0.7, Ed approached Reuss model, similarly to theoretical triphasic materials. Hashin-Shtrikman bounds is not perfectly applied to theoretical biphasic materials under dynamic situations.

Diaminomaleonitrile (DAMN) is an electron-rich ligand which is commonly used in the synthesis of purines, amides and Schiff base ligands. In the last case lies the interest in this molecule, given its symmetry and apparent facility to form various ligands and complexes of interest in fields such as organic solar cells and catalysis among others. Nevertheless, its bisubstitution with aldehydes displays certain difficulty due to the double conjugated presence of the nitrile group (C≡N) in its structure, which significantly affect its coordination behavior by modulating the chemical reactivity of its amines. In addition to presenting a practical resume of guidelines for the preparation of different bisubstituted compounds from DAMN, this paper reviews the possibility of attaining a precise characterization by simple spectroscopic techniques. We provide an additional discussion for one of these techniques (commonly reported but often overlooked), given its potential to provide both the symmetry and E/Z configuration of the product. We hope the comprehensive evidence discussed and shown in this review will be helpful to further develop and understand the products derived of this interesting molecule in their broad applications.

Development of non-conventional hybrids (NCHs) responds to the demand for the Elotes Occidentales 'EO' race for production of pozole. The effect of: crop cycle (2019, 2020 and 2021) on physical characteristics, flowered grain quality and phytochemical content of two HNC (Pz1 and Pz2) of pozolero maize, as well as the effect of the presence or absence of pedicel, type of pollination (open and controlled, 2019), and progenitor lines (female and male, 2020) on flowered grain quality and content of phytochemical compounds were evaluated. Size, hardness, color, total phenols and anthocyanins in unprocessed grain were determined, and yield, volume and puncture strength in flowered grain. Results were analyzed with a factorial arrangement in a completely randomized design. There were significant differences (p≤0.05) in most of the variables studied by effect of crop cycle and genotype. NCHs had large grains (40 g 100 grains-1), soft endosperm (IF> 60), pink-purple color, and phenol and anthocyanin contents similar to those reported for the 'EO' race. The presence or absence of the pedicel did not affect flowered grain quality. Controlled pollination favored anthocyanin synthesis. The anthocyanin content of NCHs was determined by the female line. Thermal processing reduced anthocyanins by 60%; however, they leached into the flowering broth, so that the pozole made from NCHs improves the nutraceutical value of the pozole, relative to that of pozole made with Cacahuacintle maize.

During 2010, at the Facultad de Medicina Veterinaria y Zootecnia of the Universidad Nacional Autónoma de México (fmvz-unam) we analyzed the influence of metadata over its website according to the search engines used by the academic community. This document serves only the second specific objective of the research: to know the academic profile, the informative behavior and the veterinary information needs of the academic community of the fmvz-unam. The methodological tool was the design and implementation of an online survey. We received 215 responses, two thirds answered academic staff, the rest, undergraduate and postgraduate students. In relation to information behavior, an Internet-usage index was developed, with which it was determined that 64 % of this community uses four or five information services on the Internet, This means that the network is widely used to seek information and as communication media. This community search for more veterinary information related to dogs, dairy cattle and sheep, compared to other animal species; while animal welfare, zoonosis and molecular biology are the topics of greatest interest.

In this paper we establish information theoretical bridges between 1) Thermal Heisenberg uncertainties $\Delta x \Delta p$ (at temperature $T$), and 2) LMC structural quantifiers. After having achieved such purpose, we determine to what an extent our bridges can be extended to both the semi classical and classical realms. Also, we find a strict bound relating a special LMC structural quantifier to quantum uncertainties.

In this review we summarize existing trends of flow control used to improve the aerodynamic efficiency of wings. We first discuss active methods to control turbulence, starting with flat-plate geometries and building towards the more complicated flow around wings. Then, we discuss active approaches to control separation, a crucial aspect towards achieving high aerodynamic efficiency. Furthermore, we highlight methods relying on turbulence simulation, and discuss various levels of modelling. Finally, we thoroughly revise data-driven methods, their application to flow control, and focus on deep reinforcement learning (DRL). We conclude that this methodology has the potential to discover novel control strategies in complex turbulent flows of aerodynamic relevance.

A large share of the reinforced concrete (RC) building stock in Mediterranean countries faces a dual challenge of seismic vulnerability and energy inefficiency, calling for urgent renovation efforts. While energy upgrades have been the focus of previous renovation policies, recent research highlights the critical need for integrated retrofitting solutions that address both structural integrity and energy performance. Multi-criteria decision-making (MCDM) approaches are a promising tool for optimizing the combined choice of these integrated interventions, considering various decision variables (DVs) of economic, social, environmental, and technical nature. To understand the impact of climate and seismic hazard conditions on multi-criteria-based retrofitting assessment, a case-study RC school building is selected and assumed to be located in three distinct climate conditions, cold, mild, and warm, and three seismic hazard levels, low, medium and high. Moreover, given the complexity and challenges of quantifying seismic performance metrics for practitioners, an available simplified (practice-oriented) approach is compared herein with a more thorough research-based one for quantifying the seismic performance of RC buildings within the MCDM framework. Both approaches are applied to the case-study building, considering twelve possible combinations of energy and seismic interventions. The accuracy of the practice-oriented approach and its impact on the retrofitting rankings is evaluated, emphasizing the importance of accessible and efficient evaluation methods in facilitating informed decision-making for building renovation

The Standard Model is not a complete description of reality; it omits the existence of dark matter, dark energy, and an explanation as to why no CP violation has been observed. However, some of these phenomena could be explained through a new force mediated by a new boson. If such a boson were massless it would result in a power law potential and if massive the interaction would be Yukawa-like. A previous experiment employing a micro-mechanical oscillator and a spherical test mass interactions was successful in placing the best limits on a mass-mass Yukawa-like interaction, but the data was never analyzed in the context of a power law. Here that data is analyzed considering a power law for powers n = 1-5 where n is the number of boson exchanges. The results show that the limits obtained through power law analysis of this data are not better than the currently accepted limits. A discussion of an experiment design capable of producing better limits on power law extensions to the Standard Model is presented, and suggests micro mechanical oscillators based experiment remains capable of improving the limits by at least one order of magnitude.

Recently, we demonstrated the validity of anomalous numbers law, known as Newcomb-Benford´s law, at the mammalian neuromuscular transmission, considering different extracellular calcium concentrations . The present work continues to examine how alterations in extracellular solution modulate the first digit law in the context of the spontaneous release of acetylcholine from the neuromuscular junction. We investigated if the intervals of miniature potentials collected at the neuromuscular junction obey the law in a hyperkalemic environment. The analysis showed that the interval between the miniature potentials at high potassium concentrations follows Newcomb-Benford´s law. Also, our data allowed us to uncover a conformity fluctuation as a function of the number of intervals of the miniature potentials. Finally, we discuss the biophysical implications of the present findings.

Circular RNAs (circRNAs) are single-stranded RNA molecules often circularized by backsplicing. Growing evidence implicates circRNAs in the underlying mechanisms of various diseases, such as Alzheimer's and Parkinson's disease (PD) - the first and second most prevalent neurodegenerative disorders. Several circRNAs are associated with brain damage, including circSNCA, circHIPK2, circHIPK3, and circSLC8A1. Gain-of-function and loss-of-function studies on circRNAs have shed light on their roles in the pathobiology of various diseases. Gain-of-function approaches typically employ viral or non-viral vectors that hyperexpress RNA sequences capable of circularizing to form the specific circRNA under investigation. In contrast, loss-of-function studies utilize CRISPR/Cas systems, antisense oligonucleotides (ASOs), or RNAi techniques to knockdown the target circRNA. Given that aberrantly expressed circRNAs have been associated with brain pathologies, a critical question arises: could circRNAs serve as viable targets for neuroprotective treatments? Translating any oligonucleotide-based therapy, including those targeting circRNAs, involves developing adequate brain delivery systems, minimizing off-target effects, and addressing the high costs of treatment. Nonetheless, RNAi-based FDA-approved drugs have entered the market, and circRNAs have attracted significant attention and investment from major pharmaceutical companies. Spanning from bench to bedside, circRNAs present a vast opportunity in biotechnology for oligonucleotide-based therapies designed to slow or even halt the progression of neurodegenerative diseases.

A description is provided of a method -- the Set Equality Method (SEM) -- to determine the validity, or lack of validity, of each categorical syllogism. A justification is given for the presentation of a new method to solve a problem which has already been solved using different approaches. First, the SEM assigns an equality of certain sets (or two of those equalities in specific cases as will be indicated) to each of the categorical propositions composing each syllogism considered -- that is, to each of the two premises and to the conclusion. Each syllogism considered is valid if and only if a) it is possible to select one of those equalities corresponding to one of the premises such that one of its members is a certain set and the other of those equalities corresponding to the other premise such that one of its members is a subset of the set mentioned, and b) it is possible to deduce an equality corresponding to the conclusion of the two equalities corresponding to the premises. In some cases, as will be specified, it is possible to provide a second test for the validity of a syllogism whose validity was already proven, thus providing information about the logical form of categorical syllogisms.

This paper describes the design and implementation of an ultrasonic non-contact air-coupled technique (UNCACT) using antisymmetric Lamb waves (ALW) for NDT assessment in novel composite sandwich plates of the car body shell. This technique is complemented with a C-Scan image implementation using this kind of guided waves. The finite element method using Comsol 6.1 is developed for the interpretation of the several wave modes presented in the experiments, including the ALW mode. The phase velocity method (PVM) is applied for the verification of the ALW mode in the portion of the RF signal necessary in the C-Scan image.

Keywords: Oral health, diabetes, periodontal disease, caries, periodontitis.

A study to produce cellulose nanofibrils (CNF) from Kraft cellulose pulp, an optimal enzyme mixture, was defined using a centroid simplex mixture design. The enzyme blend contains 69% endoglucanase and 31% exoglucanase. The central composite rotational design (CCRD) optimized the CNF production process by achieving a higher crystallinity index. It thus corresponded to a solid loading of 15 g/L and an enzyme loading of 0.974. Using the Segal formula, the crystallinity index (CrI) of CNF was determined by X-ray diffraction to be 80.87%. The average diameter of nanocellulose fibers measured by scanning electron microscopy between 550 - 600 nm for the CNF prepared by enzymatic hydrolysis and between 250 - 300 nm for the CNF produced by enzymatic hydrolysis with the optimal enzyme mixture followed by ultrasonic dispersion. Finally, synergistic interactions between the enzymes involved in nanocellulose production were demonstrated, with Colby factor values greater than one.

Despite the impact that climate change is having on our planet and considering its consequences for future generations, much of the academic literature focuses on adolescent and adult percep-tions, giving little relevance to children's perceptions. Children's voices have the potential to in-fluence public opinion, which may in turn determine the direction of a new policy on the cli-mate crisis. In this context, it is urgent that we understand how children perceive this problem. This quantitative study was based on the application of 245 questionnaires to children aged be-tween 9 and 13 years old from five schools in north-eastern Portugal, more specifically in the region of Trás-os-Montes. To collect the data, we used a questionnaire with 26 questions, being 24 of closed response, Likert type, one of them open response, and one multiple choices. The da-ta were statistically treated using SPSS software. The results show that most of the children ex-press concern about the study's potential problem. However, they show some doubts and a lack of knowledge about some of the themes. We found differences between the two study cycles, with children in the 6th grade having a higher average in the understanding of the phenomenon, as well as the level of education of the parents being positively correlated with a more ecocen-tric posture. The female students also showed a slightly more ecological posture, i.e., an eco-friendlier posture. From the results obtained, we can open new paths for future research and contribute to the definition of policies and educational practices since the school has the respon-sibility to cooperate in the production of values, attitudes, and pro-environmental behaviours.

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated to them.

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

Adolescents often migrate unaccompanied by a caregiver, facing specific risks. Mentoring has been identified as a strategy with positive results for youth at risk. Its application with unaccompanied minors (UM) refugees and asylum seekers has gained momentum within EU countries receiving refugee citizens from the EU relocation program. Portugal hosts the fourth highest number of Middle East and North Africa UM refugees and asylum seekers among EU countries. Thus, it´s relevant to review strategies and intervention programs, focused on mentoring to inform future programs in Portugal supporting UM. This article aims to describe the use of mentoring strategies towards integrating UM refugees, and how this has been taking place in Portugal. This review has the potential to inform professionals, namely social education professionals involved in the Portuguese refugee relocation program and encourage the discussion about creating based mentoring-based programs for this target group.

We studied the link between carbon and water fluxes to understand the response of net ecosystem carbon exchange (NEE) to water availability conditions of three different potato water regimes cropping systems [full irrigation (FI), deficit irrigation (DI) and rainfed (RF)]. Through the eddy covariance technique, we measured CO₂ and water vapor exchanges and determined surface resistances, omega factor, and inherent water use efficiency (IWUE). Additionally, continuous plant growth determinations of leaf area index (LAI) and specific leaf area (SLA) were made over the three cropping systems. The RF potato was a net carbon source (NEE = 187.21 ± 3.84 g C m⁻²), while both, FI (NEE= −311.96 ± 12.82 g C m⁻²) and DI (−17.3 ± 4.6 g C m⁻²) were a net carbon sink. Greater sink activity is due to high fluxes of gross primary productivity (GPP) [where the GPP > ecosystem respiration (R_eco)] and evapotranspiration (ET), and the high efficiency in the exchange of carbon and water. Without water limitations, the larger canopy, with greater photosynthetic activity (GPP/R_eco > 2) as well as with low internal resistance offers a greater area for water and carbon exchange, and the highly coupled and synchronized ET – GPP fluxes are primarily controlled by the radiative environment. The lower sink capacity of the DI potato crop and the carbon source activity from the RF, are consequences of a smaller area for water and carbon exchange due to the smaller canopy, and a low IWUE from decoupled and desynchronized carbon and water exchange caused by unbalanced restrictions on ET and GPP fluxes. Specifically, at DI potato, ET remained at a high rate, while GPP was reduced by means of non-stomatal limitations. In the rainfed potato, vapor pressure deficit (VPD) played a significant role increasing midday canopy resistance (Rc) up to 13 times compared to irrigated sites, when VPD was around 0.8 kPa. In consequence, ET and GPP fluxes decreased together, but GPP decreased more than ET because of stomatal and non-stomatal limitations.

Tributyltin (TBT) is an environmental contaminant present on all continents, including Antarctica, with a potent biocidal action. Its use began to be intensified during the 1970s, being effectively banned in 2003, but remaining in the environment to this day due to several factors that increase its half-life and misuse despite the bans. In addition to the endocrine disrupting effect of TBT, that may lead to imposex induction in some invertebrate species, there are several studies that demonstrated that TBT also has an immunotoxic effect. The immunotoxic effects that have been observed experimentally in vertebrates using in vitro and in vivo models involve different mechanisms, but mainly alterations in the expression and/or secretion of cytokines. In this review, we summarize and update the literature on the impacts of TBT on the immune system, as well as discuss what still needs to be done to fill the knowledge gaps regarding the impact of this endocrine disrupting-chemical on immune system homeostasis.

Reducing the levels of toxic chemicals that cause adverse health and environmental impacts is a challenge for the international community. There is a need of a global strategy. Indeed, too often the problems associated to the exposure of chemical substances is recognized a posteriori, in the presence of consequences already observed. The prediction of the likely effects of chemical exposure on human health is based on classical tests with animals, which are time and money consuming, may deviate from an accurate prediction towards humans, and arises ethical concerns. Regulations are now considering the adoption of in silico (or computational) methods, which can be used for prioritizing substances according to the probability to be toxic for the biosphere. Several initiatives have prioritized chemicals, typically based according to some criteria, such as chemicals which may be endocrine disruptors, or persistent, bioaccumulative, or toxic (PBT). However, these initiatives focused on a certain range of adverse properties, and covered a certain number of substances only. We applied a set of largely validated and widely used predictive methods to large collections of chemicals: (i) to about 340,000 with a defined function, and (ii) to about 6 millions, which have been synthetized. The aim of this study is to quantify the putative impact of existing and future chemicals on towards human health, ecological and environment properties. The impact on the environment is the cause of major concern. This is the case of pesticides and hazardous, which is quite expected; however, also pharmacologically active candidate compounds of natural origin may have a high level of ecotoxicity. Pesticides and hazardous are also the categories of higher concern for humans, followed by pharmaceuticals. The pesticides and the hazardous are the categories of higher concern also on the environmental point of view. The results of our analysis could be the basis for the identification of new safety rules.

Marine lipids are recognized for their health promoting features, mainly for being the primary sources of omega-3 fatty acids, and therefore critical for human nutrition in an age when the global supply for these nutrients is experiencing an unprecedent pressure due to an ever-increasing demand. The seafood industry originates a considerable yield of co-products worldwide that, while already explored for other purposes, remain mostly undervalued as sustainable sources of healthy lipids, often being explored for low value oil production. These co-products are especially appealing as lipid sources since, besides the well-known nutritional upside of marine animal fat, particularly rich in omega-3 polyunsaturated fatty acids (PUFAs), they have also interesting bioactive properties, which may garner them further interest, not only as food, but also for other high-end applications. Besides the added value that these co-products may represent as valuable lipid sources, there is also the obvious ecological upside of reducing seafood industry waste. In this sense, repurposing these bioresources will contribute to a more sustainable use of marine animal food, reducing the strain on already heavily depleted seafood stocks. Therefore, untapping the potential of marine animal co-products as valuable lipid sources aligns with both health and environmental goals by guaranteeing additional sources of healthy lipids and promoting more eco-conscious practices.

The wastewater circular economy (WW-CE) promises a solution to improve water and sanitation management worldwide. However, the transition from conventional to circular wastewater treatment plants (WWTPs) requires facilitation to aid in decision makers understanding of integral sustainability impacts of alternative WW-CE configurations. This research implemented Life Cycle Sustainability Assessment (LCSA), combining Life Cycle Assessment, Social Life Cycle Assessment and Life Cycle Costing with a Multi-criteria Decision Making (MCDM) model to quantify environmental, socio-cultural, and economic impacts of conventional WWTPs with the WW-CE. Two real WWTPs in Chile have embraced the WW-CEs and adopting the title of Biofactories. These were considered as case studies, compared under three scenarios to demonstrate the sustainability trade-offs of the transition from no sanitation to conventional WWTPs and Biofactory WW-CE configurations. Results demonstrated that the transition to WW-CEs improved integral sustainability according to the LCSA model implemented in both WWPTs. This study highlights the urgent need to adopt sustainable decision-making models to not only improve sanitation coverage, but also improve sustainability performance of the sanitation industry across the globe.

Ecologists use the net biotic interactions among plants to predict fundamental ecosystem features. Following this approach, ecologists have built a giant body of theory founded on observational evidence. However, due to the limitations that a phenomenological approach raises both in empirical and theoretical studies, an increasing number of scientists claim the need for a mechanistic understanding of plant interaction outcomes, and a few studies have taken such a mechanistic approach. In this synthesis, we propose a modeling framework to study the plant interaction mechanistically. We first establish a conceptual ground to frame plant-plant interactions, and then, we propose to formalize this research line theoretically developing a family of individual-based, spatially-explicit models in which biotic interactions are an emergent property mediated by the interaction between plants’ functional traits and the environment. These models allow researchers to evaluate the strength and sign of biotic interactions under different environmental scenarios and thus constitute a powerful tool to investigate the mechanisms underlying facilitation, species coexistence, or the formation of vegetation spatial patterns.

We present new results in positron annihilation lifetime spectroscopy (PALS), thermo-optical dilatometry and microscopy, which are indicating a strong correlation between grain-boundaries and mass transport during the sintering process of carbonyl iron powder. In this particular system we were able to show that the change in particle shape and size with increasing temperature yields an anisotropy in shrinkage, which manifests itself in a higher shrinkage perpendicular to the compaction axis. In the intermediate stage of sintering, where the major mass transport occurs, the average distance between two grain boundaries could be determined to (3,73 ± 0,18) μm at T = 744°C. This is in good agreement with previous calculations of positron pathways in defect free particles. Furthermore, due to sintering temperatures far above the annealing temperature of dislocations in iron, the existence of dislocations in the bulk of the particles is very unlikely. These claims are reflected by the collected positron data, which exhibit a clear grain boundary signal of ∼ 250ps while no vacancy or dislocation signal (typically ∼ 160 ps) is evident in the intermediate stage of sintering.

Mass crises are disruptive to people's mental health. The study aimed to explore mental distress during COVID-19 quarantine in a sample of university workers in Brazil. The survey included sets of questions about demographics, health, and support, an open question about major concerns, and the Clinical Outcome Routine Evaluation (CORE-OM), a measure of mental distress. 407 professionals participated in the study: mean age of 40 years (SD = 11.2), mostly female (67.8%), married (64.8%) and fulfilling social distancing to avoid COVID-19 infection (99%). Using the Consensual Qualitative Research for simple qualitative data (CQR-M) the main areas of concern were grouped into six domains, as follows: Work, Health, Isolation, Personal life and routine, Social environment, and Future. Many responses were multiple. They form categories indicating specific concerns within these domains. Quantitative data were analyzed by identifying the simple effects of potential predictors of mental distress. The results indicated medium effects of help with household chores, psychiatric treatment, age and physical exercise. Having someone available to listen was the only variable with a large effect in reducing mental suffering. The hybrid approach showed that the psychological experience during the pandemic is quite multifaceted and complex pointing new clues for public mental health.

When a low-salience stimulus of any type of sensory modality—auditory, visual, tactile—shortly precedes an unexpected startle-like stimulus, such as the acoustic startle reflex, the startle motor reaction becomes less pronounced or is even abolished. This phenomenon is known as prepulse inhibition (PPI), and it provides operational measures of information processing by filtering out irrelevant stimuli. Because PPI implies plasticity of a reflex and is related to automatic or attentional processes, depending on the interstimulus intervals, this behavioral paradigm might be considered a potential marker of short- and long-term plasticity. Assessment of PPI is directly related to the examination of neural sensorimotor gating mechanisms, which are plastic adaptive operations for preventing overstimulation and help the brain focus on a specific stimulus among other distracters. Despite their obvious importance in normal brain activity, little is known about the intimate physiology, circuitry, and neurochemistry of sensorimotor gating mechanisms. In this work, we extensively review the current literature focusing on studies that used state-of-the-art techniques to interrogate the neuroanatomy, connectomics, neurotransmitter-receptor functions, and sex-derived differences in the PPI process, and how we can harness it as biological marker in neurological and psychiatric pathology.

Lineage diversity can refer to the number of genetic lineages within species or to the number of deeper evolutionary lineages, such as genera or families, within a community. Community lineage diversity (CLD) is of interest to ecologists, evolutionary biologists, biogeographers, and those setting conservation priorities. Despite its relevance, it is not clear how to best quantify CLD. With North American tree communities as an example, we test which taxonomic and phylogenetic metrics best measure CLD. We find that phylogenetic metrics outperform taxonomic metrics. Faith’s phylogenetic diversity performs well, but is skewed towards the number of lineages in recent time. The best metric is newly derived here, and termed time integrated lineage diversity (TILD). Mapping the lineage diversity of tree communities across the contiguous United States, we find a spatial pattern differing from that of species richness in key areas. The Pacific Northwest, Great Lakes Region, state of Maine, and south-eastern piedmont and coastal plain forests all emerge as areas high in lineage diversity, but relatively lower in species richness. We urge the consideration of lineage diversity, as well as species richness, when setting conservation priorities.

Social networks have become the scenario with the greatest potential for the circulation of disinformation, hence there is a growing interest in understanding how this type of information is spread, especially in relation to the mechanisms used by disinformation agents such as bots, trolls, among others. In this scenario, the potential of bots to facilitate the spread of disinformation is recognised, however, the analysis of how they do this is still in its initial stages. Taking into consideration what was previously stated, this paper aimed to model and simulate scenarios of disinformation propagation in social networks caused by bots based on the dynamics of this mechanism documented in the literature. For achieving the purpose, System dynamics was used as the main modelling technique. The results present a mathematical model, as far as disinformation by this mechanism is concerned, and the simulations carried out against the increase in the rate of activation and deactivation of bots. Thus, the preponderant role of social networks in controlling disinformation through this mechanism, and the potential of bots to affect citizens, is recognised.

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

Byers Peninsula (62°34’-62°40’S-60°54’61°13’W), 60 km2 in size, is considered one of the largest ice-free areas in Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving effects of climate changes, limnology and microbiology, live cycles, but not albedo. Surface albedo is one of the key physical parameters in the surface energy budget of polar regions. Most of Antarctica is covered by ice sheets; only about 0.44% of the area is permanently ice-free. However, in maritime Antarctica, the ice-free areas, corresponding to small islands, peninsulas, and coastal beaches, account for about 3% of the territory. To incorporate the contribution of these areas into global albedo models, it is necessary to relate the soil properties of the ice-free areas to the surface albedo response. Also, mapping soil properties and albedo have and special interest in these ice-free areas. Image classification using machine learning methods trained with georeferenced soil data could be useful for mapping soil properties and albedo in multispectral optical satellite images. A shallow neural network implemented using the Keras Python module was used to define and train models of soil properties using 15 explanatory variables corresponding to bands and spectral indices of a Sentinel image and a population of 49 soil samples taken from the top 5 centimeters of the soil profile. The soil samples were analyzed in the laboratory and a spectral library in the Vis-Nir range (350-2500 nm) was created. The albedo of the samples was integrated from the ADS spectra. At the same time, a linear regression model of albedo using the soil properties as explanatory variables was performed. The R2 fit of this new model was about 0.82 and the error of estimation was 4.1. The model was extended to the entire Byers Peninsula using the ML soil property models as explanatory variables. The RMSE of the extended models increased up to 8.2. We think that the main cause of this increase (2.6 points) is related to the error propagation, phenomenon due to the use of models as explanatory variables. However, another important part of the error increase could be due, among other reasons, to the use of an image that, although corrected, is not completely free of clouds.

Precision medicine approaches often relies on complex and integrative analysis of multiple biomarkers from “omics” data to generate insights that can help either diagnostics, prognostics or therapeutical decisions. Such insights are often made using Machine learning (ML) models that make sample classification for a particular phenotype (yes/no). Building such models is a challenge and time-consuming, requiring advanced coding skills and mathematical modelling expertise. Artificial intelligence (AI) is a methodological solution that has the potential to facilitate, optimize and scale model development. In this work, we developed an AI-based, user-friendly and code-free platform (https://digitalphenomics.com) that fully automates the development of predictive models from quantitative “omics” data. Here, we show the application of this tool with the development of cancer survival prognostics models using real-life data from breast, lung and renal cancer transcriptomes. We report and compare their sensitivity, specificity, accuracy and Receiver Operating Characteristic (ROC) curve Area Under the Curve (AUC). Further, we report the associated sets of genes (biomarkers) and their expression pattern that are predictive of cancer survival. Moreover, we made our models available as online tools to generate prognostic predictions based on the gene expression of the biomarkers. In conclusion, we demonstrated that our tool is a robust user-friendly solution to develop bespoke predictive tools from “omics” data which facilitate precision medicine introduction to the point-of-care.

On these days, issues such as environmental degradation, wealth gap and unequal access to op-portunities and resources are increasing. These concerns have increased the need for sustainable entrepreneurship, defined as sustainable business practices. Entrepreneurship is central in transi-tioning towards a more sustainable future, whereas aligning the social, economic, and ecological objectives and ecological entrepreneurs play a role. This literature review analyzes the field of sustainable entrepreneurship and the extent of their integration in the global business arena. It aims to analyze the depth of existing pieces of literature on sustainable entrepreneurship, its defi-nitions and applications in business practices. The analysis relies upon a literature search on the SCOPUS database around the keywords ‘Sustainability’ and ‘Sustainable Entrepreneurship’. The scientific software VOSviewe is used to better ilustrate the linkage of major categories and correspondent trends, related both with business growth and maintenance of ecological systems. It concludes that the desired levels of sustainability require collaborations between all stakehold-ers, while the transition towards service‐oriented business models has contributed to the growth of sustainable entrepreneurship. Nevertheless, existing institutional structures favor current unsustainable businesses and systems over the newer sustainable ones, demanding from eco-preneurs to initiate institutional changes

In the early 1980s it was well established that Leray solutions of the unforced Navier-Stokes equations in Rn decay in energy norm for large time. With the works of T. Miyakawa, M. Schonbek and others it is now known that the energy decay rate cannot in general be any faster than t^-(n+2)/4 and is typically much slower. In contrast, we show in this note that, given an arbitrary Leray solution u(.,t), the difference of any two Stokes approximations to the Navier-Stokes flow u(.,t) will always decay at least as fast as t^-(n+2)/4, no matter how slow the decay of || u(.,t) ||_L2 might happen to be.

Artificial Intelligence based on Deep Learning is opening new horizons in Biomedical research and promises to revolutionize the Microscopy field. Slowly, it now transitions from the hands of experts in Computer Sciences to researchers in Cell Biology. Here, we introduce recent developments in Deep Learning applied to Microscopy, in a manner accessible to non-experts. We overview its concepts, capabilities and limitations, presenting applications in image segmentation, classification and restoration. We discuss how Deep Learning shows an outstanding potential to push the limits of Microscopy, enhancing resolution, signal and information content in acquired data. Its pitfalls are carefully discussed, as well as the future directions expected in this field.

Background: There is limited data on gender-based differences in atrial fibrillation (AF) treatment and prognosis. Our aim was to examine gender-related differences in medical attention in emergency department (ED) and follow-up (FU) among patients diagnosed with an AF episode and to determine whether there are gender-related differences in clinical characteristics, therapeutic strategies and long-term adverse events in this population. Methods: We performed a retrospective observational study of patients who presented to a tertiary hospital ER for AF from 2010-2015, with a minimum FU of one year. Data on medical attention received, mortality and other adverse outcomes were collected and analyzed. Results: Among the 2 013 patients selected, 1232 (60%) was female. Women were less likely than men to be evaluated by a cardiologist during the ED visit (11.5% vs. 16.6%, p=0.001) and were less likely to be admitted (5.9% vs. 9.5%, p<0.05). Electrical cardioversion was performed more frequently in men, both during the first episode (3.4% vs. 1.2%, p=0.001) and during FU (15.9% vs. 10.6%, p<0.001), in spite of a lower AF recurrence rate in women (9.9% vs 18.1%). During FU, women had more hospitalizations for heart failure (26.2% vs. 16.1%, p<0.001). Conclusions: In patients with AF, although no gender differences in mortality, there were significant differences in clinical outcomes, medical attention received, and therapeutic strategies. Women underwent fewer attempts at cardioversion, had a lower probability of being evaluated by cardiologists and showed a higher probability of hospitalization for heart failure. Being alert to these iniquities should facilitate to adopt measures to correct them.

Current State-of-the-Art (SotA) chatbots are able to produce high quality sentences, handling different conversation topics, and larger interaction times. Unfortunately, the generated responses highly depend on the data on which they have been trained, the specific dialogue history and current turn used for guiding the response, the internal decoding mechanisms, ranking strategies, among others. Therefore, it may happen that for semantically similar questions asked by users, the chatbot may provide a different answer, which can be considered as a form of hallucination or produce confusion in long-term interactions. In this research paper, we propose a novel methodology consisting of two main phases: a) hierarchical automatic detection of topics and subtopics in dialogue interactions using a Zero-Shot learning approach, and b) detecting inconsistent answers using K-Means and the Silhouette coefficient. To evaluate the efficacy of topic and subtopic detection, we used a subset of the DailyDialog dataset and real dialogue interactions gathered during the Alexa Socialbot Grand Challenge 5 (SGC5). The proposed approach enables detecting up to 18 different topics and 102 subtopics. For the purpose of detecting inconsistencies, we manually generate multiple paraphrased questions and employ several pre-trained SotA chatbot models to generate responses. Our experimental results demonstrate a weighted F-1 value of 0.34 for topic detection, a weighted F-1 value of 0.78 for subtopic detection in DailyDialog, then 81% and 62% accuracy for topic and subtopic classification in SGC5; finally, to predict the number of different responses, we obtained a mean squared error (MSE) of 3.4 when testing smaller generative models and 4.9 in recent large language models.

Abstract: (1) Background: tuberculosis presents an epidemiological trend towards inequality, especially among people in social exclusion and situations of vulnerability. To analyze territories where there is a concentration of people diagnosed with tuberculosis, in a street situation, and who make chronic use of alcohol, tobacco, and illicit drugs. We will also analyze trends in this health condition in southern Brazil; (2) Methods: Ecological study, developed in the 399 municipalities of Paraná, Southern Brazil, with all tuberculosis cases in the homeless population registered in the Information System of Notifiable Diseases between 2014 to 2018. For data analysis, we used descriptive statistics, for the time series, the Prais-Winsten autoregression method, whereas for spatial analysis, we used the Getis-Ord Gi technique*; (3) Results: in total, 560 cases were reported. We found a predominance of alcohol, smoking, and illicit drugs users, with an increasing trend in the state and clusters of spatial risk in the East health macro-region; (4) Conclusions: We observed territories with critical levels of highly vulnerable people who use psychoactive substances and are in a street situation. The results highlight the importance of incorporating public policies of social protection to these individuals and resolutive health services that receive and assist in eradicating TB.

Music perception in foetuses has been explored under different theoretical paradigms such as habituation, categorical perception, sound preferences and recall. This study investigated the temporal dimension of music perception through the habituation and sensitization paradigm. Foetuses of 41 pregnant women, mean gestational age of 34.7 weeks (±2.4), were observed during ultrasound exams. Foetuses’ reaction to two different tempos (Allegro vs Adagio) and sources (internal vs external) of music stimuli was registered by heart rate variability (HR) and motor response according to the Assessment of Preterm Infants Behaviour scale (APIB) by its factors of movement (MOV) and organization (ORG). A folkloric lullaby, sung and played live with a stringed instrument by a musician, was presented in three stages that were compared to baseline: 1) slow tempo (Adagio), 2) fast tempo (Allegro); and 3) now sung by mother at slow tempo (Adagio). Exploratory analyses showed that all factors increased from baseline to first stage. HR and ORG varied significantly among stages, with HR being the strongest factor. MOV merely detected change from baseline to first stage. ORG decreased for Allegro but increased for maternal Adagio, while HR decreased to near baseline values. ANOVA-repeated measures with gestational age as covariate showed that all measures were sensitive to first music presentation (Adagio), although only HR and ORG differed among stages. Considering estimated marginal means, adjusted for gestational age, HR presented a sensitization pattern throughout stages, but ORG kept habituating to external source and increased to maternal Adagio, suggesting foetal discrimination by sound source. We conclude that foetuses showed different behavioural and physiological responses to external versus internal sound source and musical tempo. The combined use of a behavioural scale (APIB) and HR in foetuses proved to be a valid multidimensional instrument.

Super-Resolution Microscopy enables non-invasive, molecule-specific imaging of the internal structure and dynamics of cells with sub-diffraction limit spatial resolution. One of its major limitations is the requirement for high-intensity illumination, generating considerable cellular phototoxicity. This factor considerably limits the capacity for live-cell observations, particularly for extended periods of time. Here, we overview new developments in hardware, software and probe chemistry aiming to reduce phototoxicity. Additionally, we discuss how the choice of biological model and sample environment impacts the capacity for live-cell observations.

This study investigated the development of Aedes aegypti density in houses of the urban locality of Poblado Miguel Alemán Valdes, in the Sonora state of Mexico, after application of 1% propoxur paint as full wall coverage (IP) and targeted indoor painting (IP 1m) in comparison to IRS with propoxur 70% WP (full wall coverage). The 1% propoxur paint was applied by the homeowners by brushing and rolling at the recommended dose of 1L/8 m², equivalent to 1.5 g a.i./m², while IRS was conducted by professionals with Propoxur 70% WP at a dose of 1 g a.i./m². Adult mosquito surveys were conducted in a random sample of houses in each block one week before the interventions and at week 1, month 1 to 4, month 6, month 9 and month 12 post-interventions. All three propoxur based treatments provided similar reductions (43.7%, 44.9% and 41.3% for IP, IP 1m and IRS respectively) in the fraction of houses positive in female Aedes aegypti resting indoor and outdoor as one year average of 8 follow up surveys. Indoor resting density of Aedes females during the one-year evaluation was reduced by 77.5% through IP followed by IP 1m with 64.2% reduction and 30% reduction with IRS. Culex mosquitoes’ interior density was affected as well by the insecticide treatments with similar average reductions for IP 1m (50.0%) and IRS (57.8%) in comparison with control. Aedes breeding was impacted by the insecticide paint in similar extent for both interventions, expressed by a substantial reduction of the House Index (20.1% IP, 31.2% IP 1m) and especially the Container Index (51.8% IP, 61.7% IP 1m) during the one-year surveys in comparison to control. In contrast, IRS treated block experienced an increase in both indexes. However, despite IP and IP 1m impacted in Aedes adult and immature indexes with noticeable reductions, the differences in all cases were not significative among the different insecticide treatments. The low sample size and mosquito population levels may have influenced the statistical outcomes. More than 80% of the interviewed residents were satisfied with the effectiveness of the paint and IRS treatments. The determination of the blood cholinesterase activity of tested individuals after the use of the carbamate paint and IRS in this study did not exceed acceptable inhibition limits. This study suggests that the application of propoxur paint by homeowners as full house coverage or as targeted indoor painting can be a safe and accepted intervention method for density reduction of Aedes aegypti populations in urban environments.

Primary ciliary dyskinesia (PCD) is an inherited disorder that impairs motile cilia, essential for respiratory health, with a reported prevalence of 1 in 16,309 within Hispanic populations. Despite having the RSPH4A [c.921+3_921+6del (intronic)] founder mutation in 70% of Puerto Rican patients, the characterization of the ciliary dysfunction remains unidentified due to the unavailability of advanced diagnostic modalities like High-Speed Video Microscopy Analysis (HSVA). Our study implemented HSVA for the first time on the island as a tool to better diagnose and characterize the RSPH4A [c.921+3_921+6del (intronic)] founder mutation in Puerto Rican patients. By applying HSVA, we analyzed the ciliary beat frequency (CBF) and pattern (CBP) in native Puerto Rican patients with PCD. Our results showed decreased CBF and a rotational CBP linked to the RSPH4A founder mutation in Puerto Ricans, presenting a novel diagnostic marker that could be implemented as an axillary test into the PCD diagnosis algorithm in Puerto Rico. The integration of HSVA technology in Puerto Rico substantially enhances the framework for PCD evaluation and diagnosis, facilitating prompt detection and early intervention for improved disease management. This initiative, demonstrating the potential of HSVA as an adjunctive test within the PCD diagnostic algorithm, could serve as a blueprint for analogous developments throughout Latin America.

African trypanosomes are an early branch in eukaryotic evolution and developed a unique endomembrane system as an adaptation to their parasitic life style. The key virulence mechanism of many pathogens is successful immune evasion to enable survival within the host, which is a feature requiring both genetic events and membrane transport in African trypanosomes. Intracellular trafficking not only plays a role in immune evasion, but also in homeostasis of intracellular and extracellular compartments and interactions with the environment. Significantly, historical and recent work has unravelled some of the connections between these processes and highlighted how immune evasion mechanisms associated with adaptations in membrane trafficking may have, paradoxically, provided specific sensitivity to drugs. Here we explore these advances in understanding the membrane composition of the trypanosome plasma membrane and organelles and provide a perspective for how transport could be exploited for therapeutic purpose.

This work presents an alternative to harnessing wind energy with an Electromagnetic Frequency Regulator (EFR) coupled to a hydrostatic transmission and associated with a horizontal axis wind turbine, a bidirectional frequency inverter and a secondary energy source, in a hybridized system. The hydrostatic transmision is composed by a fixed displacement axial piston pump and a variable displacement, swash plate, axial piston motor. Feedback linearization was used as a technique to control the motor geometric displacement, and a prediction algorithm for the steady state rotations of the armature and the electromagnetic field has been developed. A 5\,kW project was simulated on a Scilab platform, with combinations of constant or variable load, and constant or variable wind speed. The results indicated that the system was able to supply the generator load, adapting to fluctuations in wind speed. The possibility of storing wind energy through the inverter has also been proven. The system can accumulate energy in batteries during the fastest wind regimes, to use it when the turbine power is lower than the load.

Keywords: pelvic ultrasound, follicle number per ovary, FNPO, ovarian volume, PCOM, upper normal limits, referral population

Demand for niobium and tantalum is increasing exponentially as these are essential ingredients for the manufacture of, among others, capacitors in technological devices and ferroniobium. Mine tailings rich in such elements could constitute an important source of Nb and Ta in the future and so alleviate potential supply risks. This paper evaluates the possibility of recovering niobium and tantalum from the slags generated during the tin beneficiation process of mine tailings from the old Penouta mine, located in Spain. To do so, a simulation of the processes that would be required to beneficiate and refine both elements is carried out. After tin carbothermic reduction, the slags are sent to a hydrometallurgical process where at the end niobium oxide and tantalum oxide are obtained. Reagents, water and energy consumption, in addition to emissions, effluents and product yields are assessed. Certain factors were identified as critical, and recirculation was encouraged in the model to maximize production and minimize reagents use and wastes. With this simulation, considering 3000 production hours per year, the metal output from the tailings of the old mine could cover around 1% and 7.4% of the world annual Nb and Ta demand, respectively.

With an estimated 3 to 5 million human cases annually and the potential to infect domestic and wild animal populations, influenza viruses are one of the greatest health and economic burdens to our society [1] and pose an ongoing threat of large-scale pandemics. Despite our knowledge of many important aspects of influenza virus biology, there is still much to learn about how influenza viruses replicate in infected cells, for instance how they use entry receptors or exploit host cell trafficking pathways. These gaps in our knowledge are due, in part, to the difficulty of directly observing viruses in living cells. In recent years, advances in light microscopy, including super-resolution microscopy and single-molecule imaging, have enabled many viral replication steps to be visualised dynamically in living cells. In particular, the ability to track single virions and their components, in real time, now allows specific pathways to be interrogated providing new insights to various aspects of the virus-host cell interaction. In this review, we discuss how state-of-the-art imaging technologies, notably quantitative live-cell and super-resolution microscopy, are shedding new nanoscale and molecular insights into influenza virus replication and revealing new opportunities for developing antiviral strategies.

The potential of social networks for the circulation of disinformation as a strategy of diplomacy has been of great interest to the academic community, but the way in which it is propagated and modelled is still in its beginnings. This article aimed to simulate the propagation of disinformation in social networks derived from the diplomacy strategy, based on the elements of the system. For the design of the simulation model, system dynamics was used as the main technique in the research methodology in conjunction with statistical analysis. Five computational simulations were run for the adoption methods of susceptible and uninformed population, misinformation techniques and echo chamber. The developed model found that the diplomacy disinformation agent is able to spread its message efficiently through the bot outreach mechanism and only a part of the susceptible population unsubscribes to the disinformation agent's account. Significant differences were identified in the absence of paid outreach, bots and trolls in the propagation of information, and in the variation in the timing of disinformation propagation. Consequently, the developed model allows the understanding of the problem of disinformation as a strategy of diplomacy from international rather than local dynamics, as well as the effects of the use of each element in the system.

The production of biodiesel through transesterification routes generates large amounts of glycerol, approximately 10 m3 for every 90 m3 of the biodiesel produced. Taking into account this scenario, the valorization of glycerol using chemical routes that could be operated in biodiesel industry constitutes a promising approach to achieve added-value products. An interesting option is the production of ethers, which can be used as fuel additives in diesel engines to improve the combustion efficiency, reducing soot emission and increasing cetane index. In this study, a purification route was applied to crude glycerol and its valorization by etherification was evaluated. The glycerol contents of purified samples were above 98% wt. The purified and commercial glycerol was used to obtain ethers. Etherification reactions were carried out with different alcohols (ethanol, isopropanol and 3-methyl-1-butanol) into a batch reactor, using small amount of Amberlyst 15 as a catalyst, at autogenous pressure and solvent-free conditions. The glycerol conversion, selectivity and yield to ethers were evaluated. A glycerol conversion of 97% wt. with selectivity of 80% to monoether was obtained when using ethanol. For isopropanol, the glycerol conversion was up to 95% (76% of monoether and 22% of diether). However, the selectivity to ethers for 3-methyl-1-butanol was negligible (&lt;3% wt.). A process simulation for purification and etherification steps integrated with a biodiesel production was assessed in terms of productivity and energy consumption, considering different scenarios of glycerol/alcohol molar ratios.

This study was conducted with the objective of investigating the enrichment of weaned piglet diets with organic selenium (proteinate selenium) and inorganic selenium (sodium selenite) with two addition levels (0.15 and 0.30 mg/kg). A total of 40 piglets (20 castrated males and 20 females) weaned at 28 days of age with an average initial weight of 6.60±1.06 kg were used. The treatments were: Control diet (Control diet); Selenium-enriched control diet proteinate with 0.15 mg/kg of selenium added (SeOrg-0.15); Selenium-enriched control diet proteinate with 0.30 mg/kg of selenium added (SeOrg-0.30); Control diet enriched with sodium selenite with 0.15 mg/kg of selenium added (SeInorg-0.15); and Control diet enriched with sodium selenite with 0.30 mg/kg of selenium added (SeInorg-0.30). The presence of selenium in the control diet came from the ingredients and the mineral supplement. The following data were analyzed: productive performance; digestibility of nutrients and energy; morphometry and intestinal integrity; serum biochemical parameters; and gene expression of selenoproteins in intestinal epithelium and liver tissue of piglets. The SeOrg-0.30 treatment caused a reduction (P

The growing concern about climate change and the recognition of the planet’s limits led society to look for alternatives that promote the balance between the natural and the built environment. The circular economy emerges as an alternative to the linear economic model, inspired by natural metabolisms, by circulating resources in continuous loops, where their intrinsic value is maintained and improved. This research proposes a closed-loop strategy in the built environment by studying innovative constructive solutions that aim to find use, value, and inspiration in what is considered waste. A literature review is conducted on the circular design strategies, re-use and recycle typologies, and waste transformation processes. Then, the development of a methodology for qualitative evaluation and selection of re-used and upcycled construction materials from post-consumer waste and by-products is presented and then applied to thirty-five cases of constructive solutions from plastic, wood, paper, steel, aluminium, and agricultural waste. The research reports that the developed framework is adequate. The analysed alternative materials have good environmental performance and can be used as building materials despite their functional limitations, reflecting the enormous potential of waste as a resource for the construction industry.

The COVID-19 pandemic brought about a significant change in mobility habits within cities, with a significant decrease in the use of collective urban transport that has only been partially and unevenly reversed. To recover the previous rates of use, many cities are analyzing which characteristics of the urban transport network are hindering this recovery process in order to design actions to promote sustainable mobility. This article shows a study carried out in the city of Almería (Spain), where the operation variables of the municipal bus network have been analyzed (frequency, average vehicle occupancy, length of the lines, urban or suburban character, circularity, nodality or intermodality) to detect what aspects are more determinant on the number of users recovered. The results show that the lines that have recovered the most users in average are suburban lines, as well as the nodal lines that serve key centroids such as the university. Thus, the dependence of users on public transport would be the most important determinant in recovery, more than other variables representative of the service´s intrinsic quality. This result shows that, without compromising the necessary quality of the service, the restrictions on less sustainable transportation alternatives will be those that, to a greater extent, allow for the prompt recovery of the space lost by urban public transportation.

The motion of Unmanned Surface Vehicles (USVs) is frequently disturbed by the ocean wind, wave and current. A poorly designed controller will lead to failures and even safety problems during actual navigation. In order to obtain satisfied control performance of the motion for the USVs, a Model Predictive Control (MPC) based on improved Nonlinear Disturbance Observer (NDO) is proposed. Firstly, the USV model is approximately linearized and MPC is designed for the multivariable system with constraints. In order to compensate the influence of disturbances, an improved NDO is designed, with which the calculation time for the MPC saved a lot. Finally, comparison experiments are conducted between the MPC with NDO and the MPC with improved NDO, and the results show that they have similar performance to the USVs. However, the proposed method has less parameter to be tuned and it is much more time-saving compared to the MPC with traditional NDO.

Computational Fluid Dynamics (CFD)-based simulation has been the traditional way to model complex industrial systems and processes. One very large and complex industrial system that has benefited from CFD-based simulations is the steel blast furnace. The problem with the CFD-based simulation approach is that it tends to be very slow to generate data. The CFD-only approach may not be fast enough for use in real-time decision-making. To address this issue, in this work, the authors propose the use of machine learning techniques to train and test models based on data generated via CFD simulation. Regression models based on neural networks are compared to tree boosting models. In particular, several areas (tuyere, raceway, and shaft) of the blast furnace are modeled using these approaches. The results of the model training and testing are presented and discussed. The obtained R2 metrics are, in general, very high. The results look promising and may help to improve the efficiency of operator and process engineer decision-making when running a blast furnace.

Standard cell culture is routinely performed at supraphysiological oxygen concentrations (~18% O2). Conversely, oxygen levels in most tissues range from 1%–6% (physioxia). Such hyperoxic conditions can alter reactive oxygen species (ROS) production, energy metabolism, mitochondrial network dynamics, and response to drugs and hormones. The aim of this project was to investigate the transcriptional response to different oxygen levels and whether it is similar across cell lines, or cell-line specific. Using RNA-seq, we performed differential gene expression and functional enrichment analyses in four human cancer cell lines, LNCaP, Huh-7, PC-3, and SH-SY5Y cultured at either 5% or 18% oxygen for 14 days. We found that oxygen levels affected transcript abundance of hundreds of genes, with the affected genes having little overlap between cell lines. Functional enrichment analysis also revealed different processes and pathways being affected in each cell line. Interestingly, we found that the top differentially expressed genes are involved in cancer biology. Further, we observed several hypoxia-inducible factor (HIF) targets upregulated at 5% oxygen, suggesting a role of HIF at physiological oxygen conditions. Finally, oxygen strongly induced transcription of mitochondrial genes in most cell lines, in a cell-type specific manner too. We conclude that cellular response to oxygen is widely cell-type specific, emphasizing the importance of maintaining physioxia in cell culture.

Background: Acute ischemic stroke is among the main causes of mortality worldwide; a rapid and opportune diagnosis is crucial to improve a patient's outcome. MicroRNAs are quite useful for a rapid and accurate diagnosis.Methods: We perform both structural networks approach and a meta-analysis (using a random-effect model to evaluate the heterogeneity and risk bias, according to the PRISMA statement) to analyze the feasibility to develop a microRNA-based biomarker panel for an opportune AIS diagnosis. Results: Structural networks identify a set of eight miRNAs (miR-16, miR-124-3p, miR-484, miR-15a, miR-4454, miR-107, miR-125b-5p and miR-320b) as preliminary microRNA-based biomarker panel, from these only three microRNAs are significantly associated with the main risk factors of AIS, (miR-107: hypertension, 95% CI 9.74-53.24 p<0.0001, type 2 Diabetes mellitus, 95% CI 2.18-19.26); p=0.0008; miR-16 hypertension, 95% CI 1.26-3.56 p=0.0046, smoking, 95% CI 1.07-3.54 p=0.0277; and miR-15a hypertension, 95% CI 1.26-3.56 p=0.0046; smoking, 95% CI 1.07-3.54 p=0.0277). However, the meta-analysis reveals that data is highly heterogeneous and biased; and only microRNAs isolated from plasma samples and further processed in microarrays are the most reliable to distinguish AIS patients.Conclusions: Together our results show that although there are some miRNAs that seem to be associated with AIS, we are still far to develop a miRNA-based biomarker for AIS diagnosis and it is necessary to harmonize the protocols, results and include more populations for further studies otherwise we will remain throwing punches in the dark.

Sun-Induced chlorophyll Fluorescence (SIF) relates directly to photosynthesis yield and stress but there are still uncertainties in its interpretation. Most of these uncertainties concern the influences of the emitting vegetation’s structure (e.g., leaf angles, leaf clumping) and biochemistry (e.g., chlorophyll content, other pigments) on the radiative transfer of fluorescent photons. The Caatinga is a large region at northeast Brazil of semiarid climate and heterogeneous vegetation, where such biochemical and structural characteristics can vary greatly even within a single hectare. With this study we aimed to characterize eleven years of SIF seasonal variation from Caatinga vegetation (2007 to 2017) and to study its responses to a major drought in 2012. Orbital SIF data from the instrument GOME-2 was used along with MODIS MAIAC EVI and NDVI. Environmental data included precipitation rate (TRMM), surface temperature (MODIS) and soil moisture (ESA CCI). To support the interpretation of SIF responses we have used red and far-red SIF adjusted by the Sun’s zenith angle (SIF-SZA) and by daily Photosynthetically Active Radiation (dSIF). Furthermore, we have also adjusted SIF through two contrasting formulations using NDVI data as proxy for structure and biochemistry, based on previous leaf-level and landscape level studies: SIF-Yield and SIF-Prod. Data was tested with time-series decomposition, rank correlation, spatial correlation and Linear Mixed Models (LMM). Results show that GOME-2 SIF and adjusted SIF formulations responded consistently to the observed environmental variation and showed a marked decrease in SIF emissions in response to a 2012 drought, that was generally larger than the corresponding NDVI and EVI decreases. Drought sensitivity of SIF, as inferred from LMM slopes, was correlated to land cover at different regions of the Caatinga. This is the first study to show correlation between landscape-level SIF and an emergent property of ecosystems (i.e., resilience), showcasing the value of remotely sensed fluorescence for ecological studies.

This paper proposes the configuration of an Organic Rankine Cycle (ORC) coupled to a solar domestic hot water system (SDHWS), with the purpose of analyzing the cogeneration capacity of the system. A simulation of the SDHWS was conducted at different temperatures, observing its performance to determine the amounts of useable heat generated by the solar collector; thus, from an energy balance, the amount of heat that may be used by the ORC could be determined. The working fluid that would be suitable for the temperatures and pressures given in the system were selected. The best fluid for the given conditions of superheated vapor at 120 °C and 604 kPa and a condensation temperature of 60 °C and 115 kPa was acetone. The main parameters for the expander thermodynamic design that may be used in such ORC were obtained with the possibility of generating 443 kWh of annual electric energy, with 6.65 % global efficiency of solar to electric power, or an overall efficiency of the cogeneration system of 56.35 % with a solar collector of 2.84 m².

Preventive behavior is one of the main strategies to contain the spread of the coronavirus, understand the factors that influence adherence or hesitation to protective measures and the way the population behaves during a health crisis is of great importance. Aim: To analyze the factors associated with adherence to protection measures against Covid-19 in Brazil. Method: cross-sectional study, survey type online, between the period of August 2020 and February 2021. The population included in the study were Brazilians, aged 18 years or older. Non-probabilistic sampling was used to obtain the sample. The data was stored on the "Redcap" platform and analyzed in a descriptive and inferential approach. Results: The sample consisted of 1,516 people, women adopted 10% more protective measures than men, people with higher education level and higher income, within the age group between 40-59 years, were those who most adhered to the measures imposed by health agencies. Carrier of Asthma, Diabetes Mellitus, Systemic Arterial Hypertension, Obesity and smoking were factors that increased the adherence of protective measures in the fight against COVID-19. Conclusion: Being female, aged between 40 and 59 years, higher education, smoking, not having a religion, having health insurance, and being a carrier of chronic diseases were associated with greater adherence to protective measures against COVID-19.

This paper presents a new methodology to derive and analyze strategies for a fully decarbonized urban transport system which combines conceptual vehicle design, a large-scale agent-based transport simulation, operational cost analysis, and life cycle assessment for a complete urban region. The holistic approach evaluates technical feasibility, system cost, energy demand, transportation time and sustainability-related impacts of various decarbonization strategies. In contrast to previous work, the consequences of a transformation to fully decarbonized transport system scenarios are quantified across all traffic segments, considering procurement, operation and disposal. The methodology can be applied to arbitrary regions and transport systems. Here, the metropolitan region of Berlin is chosen as a demonstration case. First results are shown for a complete conversion of all traffic segments from conventional propulsion technology to battery electric vehicles. The transition of private individual traffic is analyzed regarding technical feasibility, energy demand and environmental impact. Commercial goods, municipal traffic and public transport are analyzed with respect to system cost and environmental impacts. We can show a feasible transition path for all cases with substantially lower greenhouse gas emissions. Based on current technologies and today’s cost structures our simulation shows a moderate increase in total systems cost of 13-18%.

Nisin, an antibacterial compound produced by Lactococcus lactis strains, has been approved by the US Food and Drug Administration to be used as a safe food additive to control the growth of undesirable pathogenic bacteria. Nisin is commonly described as a pH-dependent primary metabolite, since its production depends on growth and culture pH evolution. However, the relationship between bacteriocin synthesis and the consumption of the limiting nutrient has not been described until now. Therefore, this study aimed to develop a competitive four-dimensional Lotka Volterra-like equation to describe the relationships between culture pH, limiting nutrient (total nitrogen: TN) consumption and production of biomass (X) and nisin (BT) in four series of batch fermentation with L. lactis CECT 539 in diluted whey (DW)-based media. The developed four-dimensional LV-like equation (with a unique set of parameters) could not be used to describe all cultures belonging to each fermentation series. However, the four-dimensional LV-like equation described accurately each individual culture, providing a good description of the relationships between pH, TN, X and BT, higher values for R2 and F-ratios, lower values (&lt; 10%) for the mean relative percentage deviation modulus, with bias and accuracy factor values approximately equal to one.

The proliferation of radio frequency devices in today's society, especially in smart homes, Internet of Things devices, and smartphones, underscores the urgent need for robust identification methods to strengthen cybersecurity. This paper delves into the field of radio frequency fingerprinting to propose a Bluetooth device identification method based on the application of the Jensen-Shannon divergence to the statistical distribution of noise in Bluetooth signals. A detailed case study is performed to investigate the Bluetooth radio frequency noise recorded at 5 Gsps from different devices is investigated to define a statistical radio frequency fingerprint for each Bluetooth device. A noise model is used to extract a unique, universal, persistent, recoverable, and robust statistical radio frequency fingerprint that identifies each Bluetooth device. Then, using the Jensen-Shannon divergence, different noise signals provided by each Bluetooth device are compared with the statistical radio frequency fingerprint of all devices and a membership resolution is declared. The study shows that the proposed method can discriminate between devices of the same brand and model, achieving an identification effectiveness of 99.5 \%. By leveraging the statistical radio frequency fingerprint of Bluetooth devices, this research not only contributes to the advancement of the field of implicit device authentication systems based on wireless communication but also provides valuable insights into the practical implementation of radio frequency identification techniques that could be useful in forensic processes.

Byers Peninsula is considered one of the largest ice-free areas in Maritime Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving effects of climate changes in lives cycles, limnology and microbiology. Soils from maritime Antarctica are generally weakly developed and have chemical, physical and morphological characteristics strongly influenced by the parent material. However, biological activity during the short Antarctic summer promotes intense transference of nutrients and organic matter in areas occupied by different species of birds and marine mammals. To mapping and monitoring those areas with high biological occupation, could be very useful to have models of edaphic properties prepared from satellite images. In this approach, Deep Learning and Linear Regression models of soil properties and spectral indexes as explicative variables were performed. We training models of soil properties closely related to biological activity such as Dissolved Organic Carbon (DOC) and the iron fraction associated with organic matter (Fe). We tested the best approach to model the spatial distribution of DOC, Fe and pH by training models of Linear Regression and Deep Learning over Sentinel2 and WorldView2 images. The most robust models were used to track possible areas with ornithogenic soils as well as areas of the Byers Peninsula that could support the highest biological development.

(1) The purpose of this study was to compare the percentages of quarterly change for each of the variables analysed (height, weight, body fat percentage and muscle mass) as a function of the quarter in a sample of adolescent football players. (2) The sample consisted of young male football players of different categories belonging to a high-performance football academy, (more than 5 years in football and have spent 1 full year at the academy). (3) Two-way repeated measures ANOVA revealed for the anthropometric variable, P_value

Due to the severe environmental impact of the CO2 emissions associated with the production of Ordinary Portland Cement (OPC) and the increasing demand for this commodity material, the development of alternative products has become a global concern. One alternative to OPC, or alitic-based clinkers, are amorphous-wollastonitic low calcium hydraulic binders (AWLCs). This new class of hydraulic binders, described in the literature for the first time in 2015, may significantly reduce the CO2 emissions associated with its production, resulting from its lower calcium content, but also from the fact that its production technology can be fully electrified. In this paper it is provided a state-of-the-art review, providing a comprehensive description on the latest research, summarizing both the physico-chemical and mechanical characteristics for this type of hydraulic binders, as well as possible routes for its production at an industrial scale.

Computers have evolved over the years and as the evolution continues, we have been ushered into an era where high-speed internet has made it possible for devices in our homes, hospital, energy and industry to communicate with each other. This era is what is known as the Internet of Things (IoT). IoT has several benefits in the health, energy, transportation and agriculture sectors of a country’s economy. These enormous benefits coupled with the computational constraint of IoT devices which makes it difficult to deploy enhanced security protocols on them make IoT devices a target of cyber-attacks. One approach that has been used in traditional computing over the years to fight cyber-attacks is Intrusion Detection System (IDS). However, it is practically impossible to deploy IDS meant for traditional computers in IoT environments because of the computational constraint of these devices. In this regard, this study proposes a lightweight IDS for IoT devices using an incremental ensemble learning technique. We used Gaussian Naive Bayes and Hoeffding tree to build our incremental ensemble model. The model was then evaluated on the TON IoT dataset. Our proposed model was compared with other state-of-the-art methods proposed and evaluated using the same dataset. The experimental results show that the proposed model achieved an average accuracy of 99.98\%. We also evaluated the memory consumption of our model which showed that our model achieved a lightweight model status of 650.11KB as the highest memory consumption and 122.38KB as the lowest memory consumption.

Early development in mammals is characterized by the ability of each cell to produce a complete organism plus the extraembryonic, or placental, cells, defined as pluripotency. During subsequent development, pluripotency is lost, and cells begin to differentiate to a particular cell fate. This review summarizes the current knowledge of pluripotency features of bovine embryos cultured in vitro, focusing on the core of pluripotency genes (OCT4, NANOG, SOX2, and CDX2), and main chemical strategies for controlling pluripotent networks during early development. Finally, we will discuss the applicability of manipulating pluripotency during morula to blastocyst transition in cattle species.

We consider a random dynamical system arising in a model of associative memory. This system can be seen as a small (stochastic and deterministic) perturbation of a determinstic system having two weak attractors which are destroyed after the perturbation. We show, with a computer aided proof, that the system has a kind of chaotic itineracy. Typical orbits are globally chaotic, while they spend relatively long time visiting attractor's ruins.