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Resumo A biópsia endomiocárdica (BE) é o procedimento de preferência para o diagnóstico de rejeição pós-transplante cardíaco. A técnica de biótomo rígido tem sido usada devido à sua maior simplicidade e tem sido criticada pelo risco potencial de regurgitação tricúspide (RT). Nosso objetivo foi revisar todas as BEs realizadas por meio dessa técnica em um centro terciário e estimar a taxa de complicações e/ou agravamento por RT. Estudo transversal, retrospectivo, anterógrado. Os dados foram coletados de 729 BEs realizadas em 55 pacientes pós-transplante cardíaco, com um biótomo rígido Scholten Novatome™ entre setembro de 2012 e março de 2022. Todas as BEs foram realizadas pela veia jugular direita sob anestesia local e por meio de micropunção e orientação por ultrassom. Um total de 729 procedimentos tiveram ecocardiografia realizada antes e depois dos procedimentos. A estimativa da RT foi categorizada como ausente, mínima, leve, moderada e grave. O teste qui-quadrado de McNemar foi usado para analisar o grau de RT pré e pós-BE. Houve piora suficiente para se tornar RT moderada ou grave pós-biópsia em 2 (0,27%) procedimentos, e houve uma ligeira alteração na RT de mínima para leve em 25 (3,42%) procedimentos. Em 729 BEs percutâneas realizadas com um biótomo rígido, não houve perfuração miocárdica, tamponamento cardíaco ou pneumotórax. Uma morte ocorreu dentro de 24 horas após o procedimento, por motivo desconhecido. A BE com biótomo rígido é segura e não foi associada à piora da RT no acompanhamento de 729 BEs realizadas após transplante cardíaco. A taxa geral de complicações, incluindo RT moderada a grave, foi de 0,81%. A taxa de mortalidade foi de 0,14%.

SUMMARY: The objective of this study was to determine the appropriate number of replicates to identify significant differences in carcass and cut yields in broiler chickens. At 42 d of age, a total of 480 broiler chickens were selected, weighed, and processed to obtain the hot carcass yield. Subsequently, after cooling, the cold carcass yield was determined. The cold carcass was dismembered into boneless and skinless breast, tenders, legs, and whole wings, which were individually weighed to obtain the cuts yield. The collected data underwent normality analysis and subsequent determination of descriptive statistics, as well as analysis of variance, in both cases to determine mean values, standard deviation, and coefficient of variation (CV). The required number of replicates to detect differences between means for different magnitudes was determined. The CVs obtained were stable, with the highest CV observed for tenders’ yield (11.34%) and the lowest for the hot carcass (2.35%). To achieve significant differences in both, cold and hot carcass, a minimum of 8 replicates is needed for 5% differences in 97% of experiments. For breast fillet characteristics, 10 replicates are required to detect a 10% difference in 99% of experiments. Due to higher variation, tenders yield necessitates at least 10 replicates to detect a 20% difference in 90% of cases. For wing yield, 8 replicates suffice for 94% accuracy when differences exceed 15%. Lastly, 10 replicates enable detection of 7.5% differences in leg variables in 95% of experiments. Effective experimental planning, based on the statistical power of the test, is essential for determining the requisite number of replicates. Researchers must prioritize the specific carcass characteristic relevant to their study and design the number of replicates, accordingly, ensuring more reliable and realistic results.

Abstract Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

Groundwater is considered an important source of water aid for human consumption. However, this water can be contaminated by impurities, such contamination spots that might reach the water tables. The aim of this study was to investigate the quality of shallow groundwater in Flores neighborhood, located in the municipality of Benevides, within Belém metropolitan region, State of Pará, Brazil. Recommendations described in Standard Methods for Examination of Water and Wastewater were followed at the time to determine physical-chemical parameters such as potential hydrogen (pH), electrical conductivity (EC), total dissolved solids (TDS), apparent color, turbidity, total hardness (TH), ions and trace elements. Multivariate statistical analysis has shown that most predictive water-quality parameters set for human consumption are associated with natural events involving weathering and leaching processes. Nevertheless, parameters of nitrate, phosphate, EC, TDS and pH are also influenced by anthropic conditions in the surroundings, mainly phosphate and nitrate ions. Therefore, it can be concluded that shallow groundwaters in Flores neighborhood are unsuitable for human consumption, making it necessary for municipal public authorities to take action to solve the problem of water shortage in the borough, thus preventing the population from use those shallow groundwaters, as their consumption can bring health problems.

Abstract Eustachys presents lower diversity in the Old World than in the Neotropics and it occurs disjunctly between main tropical regions. This qualifies Eustachys as a good model to test whether lineages expand their niches during the process of range expansion. We performed ancestral range reconstruction, compared environmental spaces of the different geographic areas and assessed bioclimatic trait evolution. Ancestral range reconstruction indicated that most speciation in Eustachys occurred in the South America. Ancestral climatic niches of the New World are different from those of African and Australasia lineages. Our results show that Eustachys experienced niche expansion when it reached the New World. Evolutionary history of Eustachys illustrates how the range expansion promoted climatic niche shifts, which could drive unbalanced species richness of the genus among different tropical regions.

The central question of this study concerns the emergence of the Russian development model over the past decade. It highlights that this development model could be a blueprint for other emerging markets. Russia is one of the leaders of the Fourth Industrial Revolution, having improved its standing in international ratings for quality of life, human development, sustainable development, innovation, and high technology. Russia's experience can be helpful to developing countries. We study and evaluate innovation in a digital business society amid technological turmoil competing with artificial intelligence. We focus on the digital competitiveness index, the density of robots in industry, and unemployment, thereby building a novel comprehensive dataset of the economy's systemic socioeconomic and technological development under the conditions of the Fourth Industrial Revolution. We draw attention to Russia's new business environment that exhibits valuable specifics (e.g., emerging institutions and imperfect competition as clouds in the business landscape) shaped by its current transitional character. We estimate that technological progress will ensure digitalization, the prevention of extended unemployment, and the achievement of full-scale automation. Russia's innovation policy has substantial advantages for emerging market settings. This study also shows that institutionalizing the new approach provides enduring digital economy advantages for emerging markets, including effectiveness, progressiveness, and sustainability.

Os buracos negros estão entre os objetos mais estranhos e curiosos previstos pela teoria da Relatividade Geral. Eles correspondem a regiões do espaço-tempo delimitadas por uma fronteira chamada de horizonte de eventos que se atravessada, torna coordenadas do tipo-tempo em coordenadas do tipo-espaço e vice-versa. Neste artigo, faremos uma revisão das principais características dos buracos negros, tendo como público-alvo estudantes e professores de graduação em física e ciências exatas. Utilizando uma abordagem que acompanha o desenvolvimento histórico desses conceitos, mostraremos que esses objetos fascinantes podem se tornar relativamente simples ao considerar uma analogia entre seus parâmetros mecânicos e variáveis termodinâmicas. Com uma breve explicação do efeito Hawking, demonstraremos a conexão entre os buracos negros e os sistemas termodinâmicos, apresentando ao final o clássico resultado da evaporação dos buracos negros.

Over the years it has been possible to notice the growth of applications for educational purposes available on digital platforms. Many of these apps are used in teaching and learning processes, however few are evaluated regarding their theoretical and practical aspects. In this context, in chemistry teaching, specifically the area of organic chemistry, it is inferred that apps can help build knowledge of this Science through visualization and interaction with them, but little is discussed about how these apps are evaluated in practice. Therefore, the present work proposes a new model based on technical and pedagogical aspects, based on evaluation models for educational digital games and Bloom’s digital taxonomy, called the educational application evaluation model (EAEM). In addition, organic chemistry applications available on the Google Play® platform through EAEM are analyzed. The results indicate that the EAEM was efficient in evaluating organic chemistry apps, configuring itself as an alternative for choosing educational apps regardless of the subject, where teachers can analyze the characteristics of the apps according to their pedagogical activities.

Abstract This study aimed to analyze the application of the Phytoplankton Community Index-PCI and Functional Groups-FG in determining the water quality of the Guamá River (Pará, Amazônia, Brazil). Samplings occurred monthly for analyses of phytoplankton and physical and chemical parameters, for two years, at the station where water was collected for human supply consumption. Seasonality influenced electrical conductivity, total suspended solids, dissolved oxygen, transparency, winds, true color, and N-ammoniacal. The ebb tide showed high turbidity and suspended solids. The density varied seasonally with the highest values occurring in September and December (61.1 ind mL-1 and 60.2 ind mL-1, respectively). Chlorophyll-a was more elevated in December (21.0 ± 4.7 µg L-1) and chlorophyll-c higher in relation to clorophyll- b indicated the dominance of diatoms. Functional Group P prevailed in the study months. Through the PCI índex the waters of Guamá River varied from reasonable to excellent and the TSI ranged from oligo to mesotrophic. The use of Functional Groups proved to be a promising tool in the determination of water quality since it covered the most abundant species in the Environment, but the PCI is not adequate to characterize Amazonian white-waters rivers, which have diatoms as the leading dominant group.

Summary: Individuals with Williams syndrome (WS), a neurodevelopmental disorder caused by hemizygous loss of 26–28 genes at 7q11.23, characteristically portray a hypersocial phenotype. Copy-number variations and mutations in one of these genes, GTF2I, are associated with altered sociality and are proposed to underlie hypersociality in WS. However, the contribution of GTF2I to human neurodevelopment remains poorly understood. Here, human cellular models of neurodevelopment, including neural progenitors, neurons, and three-dimensional cortical organoids, are differentiated from CRISPR-Cas9-edited GTF2I-knockout (GTF2I-KO) pluripotent stem cells to investigate the role of GTF2I in human neurodevelopment. GTF2I-KO progenitors exhibit increased proliferation and cell-cycle alterations. Cortical organoids and neurons demonstrate increased cell death and synaptic dysregulation, including synaptic structural dysfunction and decreased electrophysiological activity on a multielectrode array. Our findings suggest that changes in synaptic circuit integrity may be a prominent mediator of the link between alterations in GTF2I and variation in the phenotypic expression of human sociality.

Groundwater pollution is a current issue that may result in considerable negative effects on human health and the ecological balance. In the present study, the authors evaluated pollutants in groundwater in Maricá Municipality, located on the east side of Rio de Janeiro state in Brazil. The evaluated parameters were temperature, pH, electrical conductivity, Eh, dissolved oxygen, chlorides, nitrates, dissolved organic carbon, total inorganic carbon, phosphates, and total and thermotolerant coliforms. Due to the large number of evaluated points, they were divided into zones according to the respective hydrographic basin. The local accelerated urbanization accompanying income from oil production has led to uncontrolled population growth and associated groundwater pollution. The results of the present study suggest that sewage pollution of Maricá groundwater is already a significant issue. The lack of investment in basic sanitation has led to an imbalance in the local groundwater reservoir. In certain locations of the municipality, dissolved organic carbon (DOC), nutrient, and bacteria concentrations increase and spread in the aquifers because of domestic waste disposal. As aquifers are the main source of freshwater for the residents, contamination of them represents a potential threat to local public health.

The use of artificial intelligence (AI) in education is a current topic and in Chemistry teaching it has the potential to offer some benefits. This article is the first attempt to show that activities involving Chemistry can be accelerated with the help of AI. This is a propaedeutic study that aimed to analyze the contributions of the ChatGPT AI in defining chemical concepts. The research was conducted in the virtual environment of the chatbot and was carried out in four stages. The results show that ChatGPT can be used in Chemistry teaching as an aid to the teaching and learning process. Additionally, depending on the chemical concept, AI provided coherent answers but could lead students to difficulties in understanding. Finally, the use of ChatGPT in Chemistry teaching needs to be guided by a process of reflection, so that from the AI’s responses, students present critical thinking, the teacher considers it as just another resource in Chemistry teaching, besides other actions that can be developed in Chemistry teaching to ensure that the ChatGPT AI is used ethically and responsibly.

Antibiotic resistance in Gram-negative bacteria is a formidable challenge in modern medicine [...]

This paper examines the intersection of international arbitration and money laundering and corruption in jurisdictions where corruption is endemic, such as some Eastern European countries, to provide insight into the challenges and risks involved in arbitrating. Few sources have addressed the issue of money laundering and corruption in international arbitration in these jurisdictions. Given this significant research gap, the aim of this paper is to draw attention to areas where investment and international trade relations may be undermined by criminal activity. To this end, the specific methods used by money launderers were explored through a qualitative study involving ten suspected money launderers and eighteen prevention experts. The findings were then tested quantitatively. The results show that, as the number of corruption allegations in arbitration has increased, arbitrators have assumed an important role in reviewing compliance rules related to corruption. As a result, this article seeks to improve current understanding of compliance issues in arbitration in countries where corruption is prevalent and thereby identify a path for future research.

The communication channel is a critical part of the process of information degradation. In the 4K ultra-resolution video transmission domain, the communication channel is a crucial part where information degradation occurs, inevitably leading to errors during reception. To enhance the transmission process in terms of fidelity, advanced technologies such as digital video broadcasting terrestrial (DVB-T) and its evolutionary successor, digital video broadcasting terrestrial second generation (DVB-T2), are utilized to mitigate the effects of data transmission errors. Within this scenario, this research presents an innovative methodology for the temporal analysis of 4K ultra-resolution video quality under the influence of additive white Gaussian noise (AWGN) and Rayleigh channels. This analytical endeavor is facilitated through the application of concatenated coding schemes, specifically, the Bose–Chaudhuri–Hocquenghem concatenated low-density parity check (BCH-LDPC) and Reed–Solomon concatenated convolutional (RS-CONV) coders. A more comprehensive understanding of video quality can be attained by considering its temporal variations, a crucial aspect of the ongoing evolution of technological paradigms. In this study, the Structural Similarity Index (SSIM) serves as the main metric for quality assessment during simulations. Furthermore, the simulated Peak Signal-to-Noise Ratio (PSNR) values validate these findings, exhibiting consistent alignment with the SSIM-based evaluations. Additionally, the performance of the BCH-LDPC significantly outperforms that of RS-CONV under the 64-QAM modulation scheme, yielding superior video quality levels that approximate or surpass those achieved by RS-CONV under QPSK (Quadrature Phase Shift Keying) modulation, leading to an increase in spectral efficiency. This enhancement is evidenced by SSIM gains exceeding 78% on average. The computation of average gains between distinct technologies in video quality analysis furnishes a robust and comprehensive evaluation framework, empowering stakeholders to make informed decisions within this domain.

Abstract Plant community succession is generally approached with phytosociological methods, but field surveys are time-consuming, expensive, and limited to several of sites. Remote sensing offers an efficient and economical way to analyze vegetation on large extensions and in inaccessible areas. Most studies addressing remote sensing and tree community succession refer to forest physiognomies. We investigated whether structural changes that occur in non-forest physiognomies are identified by multispectral sensor images (OLI-Landsat). Thirteen 0.1-ha plots were set up in Caatinga fragments aging 10-15, 20-25, 30-35, 40-45 and >50 years to calculate the total density of individuals (TD), mean canopy height (H), total basal area (G) and total aboveground biomass (AGB). We performed correlation analyses between these structural descriptors and eight remote sensing variables (reflectance data and spectral indices) obtained from Landsat images at the end of the rainy season and during the dry season. Blue and short-wave infrared reflectances were negatively correlated with mean height, basal area and biomass, regardless of the analyzed scene (coefficients between -0.58 and -0.79). The litter layer (a non-photosynthetic vegetation component) and the soil exposure are important factors influencing the spectral data.

This paper examines how labour productivity will increase in future workplaces that employ human resources and machine technologies. This paper expands the concept of intelligent machines as systems of automating labour based on robots and artificial intelligence. Furthermore, it aims to develop recommendations for improving productivity by managing competition and marketing in current global labour markets. We model the dependence of output per worker on robots’ international distribution, the ease of hiring foreign labour, and the dependence on pay and productivity. As a result of this research, labour productivity is defined by human resource availability and not through automation. The study develops comprehensive guidance for economic policy in the global labour market for the medium-term period. Management implications include representing a vision for the future of workplaces drawn on the productivity benefits of different workplace models that stimulate growth in labour efficiency. The recommended concept validates how innovation and digitalisation reshape the workplace.

This paper examines Business to Government (B2G) corruption in China. It contributes to existing empirical analyses in several ways. First, it draws on an extensive literature review of the cultural practice of guanxi that often facilitates corruption. Second, it offers new perspectives by focusing on the much-overlooked corruption issue on a local, and municipal level. Furthermore, it is examined how the Chinese cultural practice of guanxi, in which citizens cultivate a relationship with public officials via gift-giving, contributes to this confined municipal corruption. For this reason, the introduction of performance matrices that evaluate public officials according to various indicators and the implementation of safe avenues for complaints are suggested as more immediate solutions to low-level corruption. Therefore, any anti-corruption measures should also target public officials at the local level to ensure that they do not abuse their power.

This article delves into social entrepreneurship experience and fills a void in the extant literature by determining the post-COVID perspective contribution of social entrepreneurship activities. The research presents a nuanced perspective on the potential impact of social entrepreneurship on sustainable development across various geographical areas. We highlight an essential discovery that social entrepreneurship impacts sustainable development across diverse geographical regions. When addressing the COVID-19 pandemic, we must consider economic reasoning, theoretical implications, and geographical and socio-economic factors. Such considerations would significantly contribute to our collective efforts to overcome this global crisis. Adopting a strategic and effective method towards social entrepreneurship can accelerate the achievement of SDGs and promote equitable, sustainable development.

Recently, the two-dimensional (2D) fast Fourier transform (2D-FFT) filter bank (FB) technique was proposed as an alternative to new wireless communication technologies covering several application scenarios. This technique presents similar characteristics to orthogonal time-frequency space modulation (OTFS), such as lower PAPR and robustness in high mobility scenarios; in addition, thanks to the use of filter bank modulation, the technique has a good spectral localization. In this work, we present the generalization of the 2D-FFT FB system by making changes in the waveform structure to obtain advantages in the symbol detection process. The proposed idea allows the use of low-complexity equalizers in the time-frequency (TF) domain, bringing a good performance/complexity trade-off and obtaining bit error rate (BER) results of the same order than delay-Doppler domain receivers for OTFS. Theoretical and simulation results show that it is possible to obtain a good error performance in high mobility scenarios even using simple equalizers in the TF domain combined with waveform structure adjustments.

The digital economy's neo-industrialization self-accelerates resource consumption and wide automatization inevitably envisage a technological leap. The article contributes conceptually and empirically to a systemic vision of blockchain to sort out climate change challenges and clean energy transition and simultaneously increase the productivity and efficiency of good practices. This vision covers the popularization of ecological initiatives, waste reduction, organization of sustainable investments, control over responsibilities on both fighting and forecasting climate change and clean energy transition. By embracing the notion of blockchain as a problem-solving tool for climate change and clean energy transition, the paper draws and investigates the experiences of the 36 digitally developed and 25 digitally developing economies. It also examines the effectiveness of alternative practices in Industry 4.0. The paper's findings represent a systematic vision of implementing blockchain initiatives to solve climate change and clean energy transition. An energy-efficient model with a blockchain opens up massive opportunities for ecological monitoring, supports energy transition and ameliorates economic sustainability. Since the blockchain potential is not fully unlocked, a model expanding the use of blockchain in education to train green personnel and in science to support climate innovations is proposed.

The highly automated macromolecular crystallography beamline AMX/17-ID-1 is an undulator-based high-intensity (>5 × 1012 photons s−1), micro-focus (7 µm × 5 µm), low-divergence (1 mrad × 0.35 mrad) energy-tunable (5–18 keV) beamline at the NSLS-II, Brookhaven National Laboratory, Upton, NY, USA. It is one of the three life science beamlines constructed by the NIH under the ABBIX project and it shares sector 17-ID with the FMX beamline, the frontier micro-focus macromolecular crystallography beamline. AMX saw first light in March 2016 and started general user operation in February 2017. At AMX, emphasis has been placed on high throughput, high capacity, and automation to enable data collection from the most challenging projects using an intense micro-focus beam. Here, the current state and capabilities of the beamline are reported, and the different macromolecular crystallography experiments that are routinely performed at AMX/17-ID-1 as well as some plans for the near future are presented.

Abstract Heterogeneous chemical processes occupy a pivotal position in many fields of applied chemistry. Monitoring reaction kinetics in such heterogeneous systems together with challenges associated with ex-situ analytical methodologies can lead to inaccurate information about the nature of the catalyst surfaces as well as information about the steps involved. The present work explores the possibility of kinetic measurements of chemical reactions and adsorption processes of homogeneous and heterogeneous systems through the variation of RGB intensities of digital images using a smartphone combined with a program written in Python to accelerate and facilitate data acquisition. In order to validate the method proposed, the base promoted hydrolysis of 4-nitrophenyl acetate was initially investigated. The rate constants obtained through RGB analysis (0.01854 min−1) is almost identical to that using traditional UV–Vis spectroscopy (0.01848 min−1). The proposed method was then applied to monitor the kinetics of three heterogeneous processes: (1) reduction of 4-nitrophenolate in the presence of dispersed Pd/C; (2) decomposition of methyl orange with TiO2; and (3) adsorption of rhodamine on montmorillonite. In general, the method via digital images showed high reproducibility and analytical frequency, allowing the execution of simultaneous analyses, with an accuracy comparable to UV–Vis spectrophotometry. The method developed herein is a practical and valuable alternative for obtaining kinetic data of heterogeneous reactions and processes where a color change is involved, bypassing sampling collection and processing which decreases analytical frequency and may lead to data errors.

This work compares the anticorrosive properties of DC electrodeposited CuCoNi, CuCo, and CuNi alloy coatings in a NaCl 0.5 mol L-1 solution. The results showed that j and the bath composition influenced the chemical, morphological, and electrochemical characteristics of the alloy coatings. Among all the studied coatings, the CuCo, CuNi, and CuCoNi ones produced at j = 10 A m-2, j = 60 A m-2, and j = 25 A m-2, respectively, showed the best anticorrosive performances in the saline medium, exhibiting charge transfer resistances (Rtc) higher than 2000 Ω cm2 and an electrical double layer capacitances (Cdl) lower than 8 X10-4 F cm-2. These results agree with the compact morphologies and smaller grain sizes presented by these coatings. Therefore, the anticorrosive properties of the coatings cannot be related only to the less noble metal(s) contents in the alloy but also to their morphologies.

Climate changes have become undisputed, as have their consequences for global ecosystems and mankind. The coastal areas are among the most affected areas on the planet due to their geographical location. The effects suffered by coastal areas can render the residing populations homeless, as well as compromise the continuity of the history and culture of these environments. The Marine Extractive Reserve of the city of Soure (coastal area of eastern Amazonia) stands out for housing populations that have developed an intimate relationship with nature and have knowledge that can explain people's perception of climate changes. In this context, this study investigated how local residents perceive climate change and its consequences considering different temporal and spatial scales. To this end, questionnaires were developed and applied using a 5-point Likert scale. Our results indicate that perception is shaped by socioeconomic and demographic factors, and that they are perceived on different time scales and geographic space. These findings reflect the awareness-raising efforts of the management body of this Conservation Unit and the local knowledge, derived from the relationship of the residents with the natural environment, which, together, provided the population with assertive information that favor a better understanding of this phenomenon.

Durante la pandemia de COVID-19, el método más utilizado para monitorear el exceso de mortalidad (EM) se basa en la diferencia entre las defunciones totales (DT) de 2020 a 2021 y los registros históricos de años previos. Se compara esta metodología con indicadores alternativos, como la esperanza de vida al nacimiento (EV0) y los años de esperanza de vida perdidos (AEVP), para Argentina. Los resultados de los tres métodos indican que el EM fue mayor en 2021 que en 2020, y más acentuado en varones que en mujeres. Sin embargo, el nivel de EM varía según el procedimiento y el año de referencia: varía de 9,4 a 28 % según las DT o de 5 a 24,3 % según los AEVP; mientras las EV0 caen de 0,64 a 3,35 años. Se recomienda: 1) EV0 para medir EM en términos absolutos; 2) AEVP a la mayor edad posible, en términos absolutos y relativos, y 3) comparar los resultados respecto a 2019.

Background: Leishmaniasis results in a wide spectrum of clinical manifestations, ranging from skin lesions at the site of infection to disseminated lesions in internal organs, such as the spleen and liver. While the ability of Leishmania-infected host cells to migrate may be important to lesion distribution and parasite dissemination, the underlying mechanisms and the accompanying role of host cells remain poorly understood. Previously published work has shown that Leishmania infection inhibits macrophage migration in a 2-dimensional (2D) environment by altering actin dynamics and impairing the expression of proteins involved in plasma membrane-extracellular matrix interactions. Although it was shown that L. infantum induces the 2D migration of dendritic cells, in vivo cell migration primarily occurs in 3-dimensional (3D) environments. The present study aimed to investigate the migration of macrophages and dendritic cells infected by Leishmania using a 3-dimensional environment, as well as shed light on the mechanisms involved in this process.Methods: Following the infection of murine bone marrow-derived macrophages (BMDM), human macrophages and human dendritic cells by L. amazonensis, L. braziliensis, or L. infantum, cellular migration, the formation of adhesion complexes and actin polymerization were evaluated.Results: Our results indicate that Leishmania infection inhibited 3D migration in both BMDM and human macrophages. Reduced expression of proteins involved in adhesion complex formation and alterations in actin dynamics were also observed in Leishmania-infected macrophages. By contrast, increased human dendritic cell migration in a 3D environment was found to be associated with enhanced adhesion complex formation and increased actin dynamics.Conclusion: Taken together, our results show that Leishmania infection inhibits macrophage 3D migration, while enhancing dendritic 3D migration by altering actin dynamics and the expression of proteins involved in plasma membrane extracellular matrix interactions, suggesting a potential association between dendritic cells and disease visceralization.

A significant depletion of natural energy reserves and a sharp rise in its cost of production amidst a civilizational energy crisis, greenhouse gas issue, and increasing energy consumption have called for an urgent and radical change in the global energy agenda. An idea to promote hydrogen as an alternative energy emerges from the global energy transition agenda. In this article, our aim is to assess the prospect of hydrogen, as a potential, environmentally friendly, yet expensive and technological-demanding resource, to be developed globally. The scientific novelty of the research consists in systematizing the world experience and Russian practice of implementing energy efficiency projects within the framework of public-private partnership (PPP), substantiating, and forecasting the prospects for the use of this resource in order to decarbonize the economy and solve environmental problems, as well as determining the main directions of the national energy strategy in Russia. We have developed recommendations to eliminate the identified problems that impede the increase in the energy efficiency of industrial production and operation of facilities. It is concluded that the use of “green” hydrogen obtained with the help of renewable energy sources is promising in solving environmental problems and building a climate-neutral economy characterized by zero greenhouse gas emissions. The results of the work can be useful in well-supporting hydrogen ecosystem.

Abstract The Amazon River basins present distinct natural and anthropogenic characteristics that influence the structure of stream habitats and their associated biota. The influence of these characteristics can be evaluated through different spatial scales. We aimed to assess the influence (with and without the effect of spatial-geographical factors) of local, macroscale, and land-use variables in the structure of stream fish assemblages of Amazonian catchments with different deforestation levels. A partial redundancy analysis and a reduced metrics model were used to assess these influences. With geographic-spatial effects, we verified that the macroscale and local variables explained the variation in fish composition, and, without the effects, land use also explained the variation in this composition. In the forested catchments, the biota was associated with streams with natural characteristics (e.g., leaf banks). In the deforested catchments, it was associated with land use, sandy catchments with higher soil density (higher capacity of degradation), and less complex streams (fewer leaf banks, more sand). The associated fish have life features linked to these characteristics (e.g., Gymnorhamphichthys rondoni associated with sand). This configuration seems to be a result of both the impact of land use in the catchment (i.e., increased erosion, increased sedimentation) and the naturally sandy constitution of the catchment as well, reflecting the sandy substrate.

This paper presents the impact of the decoration of reduced graphene oxide (rGO) with metallic nanoparticles to detect sulfur dioxide (SO2). Copper and platinum were employed to produce metal nanoparticles (NPs) for the chemical and physical decoration of rGO to form the nanocomposites (rGO/NPs). We optimized NP loading by varying the concentrations of metal ions and deposition times for chemical and physical decoration, respectively. The chemical decoration presents a random nanoparticle distribution on the rGO surface with a broad particle size distribution (1 to 100 nm with a majority less than 40 nm). In comparison, the physical decoration presents uniformly distributed nanoparticles with particles of a size between 1 and 20 nm, with a majority less than 10 nm. The chemically decorated structures present the best gas responses and show that lower NP loading provides better responses. The nanocomposites present responses owing to a better synergy between NPs and the rGO surface, combined with the catalytic action of the NPs on the rGO. The physical decoration allows higher NP surface coverage than the chemical one but implies a lower remaining rGO naked surface for gaseous molecule interaction. These results illustrate that the NPs’ surface and the uncovered rGO contribute to the gas response.

Despite the significant advancements in drone sensory device reliability, data integrity from these devices remains critical in securing successful flight plans. A notable issue is the vulnerability of GNSS to jamming attacks or signal loss from satellites, potentially leading to incomplete drone flight plans. To address this, we introduce SiaN-VO, a Siamese neural network designed for visual odometry prediction in such challenging scenarios. Our preliminary studies have shown promising results, particularly for flights under static conditions (constant speed and altitude); while these findings are encouraging, they do not fully represent the complexities of real-world flight conditions. Therefore, in this paper, we have furthered our research to enhance SiaN-VO, improving data integration from multiple sensors and enabling more accurate displacement predictions in dynamic flight conditions, thereby marking a significant step forward in drone navigation technology.

Amphibians and reptiles represent a considerable proportion of the vertebrate fauna in Brazil. Different blood parasitic infections have been reported in these groups, such as Haemogregarina, Hepatozoon, Trypanosoma and microfilariae. However, insufficient research on interactions between these parasites and their hosts has been carried out in some regions of the country. Samples were collected from populations of wild herpetofauna in different microhabitats throughout Brazil, totaling 111 samples of reptiles from the states of Mato Grosso and Pernambuco. We used an integrative approach, with classical microscopy, morphometry and molecular analysis, in order to identify hemoparasites present in the analyzed fauna. Genomic DNA was extracted for the PCR protocol based on the 18S ribosomal RNA gene for Hepatozoon spp. A total of 53 positives were obtained with molecular screening (47.7%), all confirmed as Hepatozoon spp. using DNA sequencing. Among positive samples, 23 slides were examined, confirming the presence of Hepatozoon spp. in 91.3% of the smears. The phylogenetic analysis performed with sequences from 43 samples resulted in a tree containing several distinct clades. Sequences were generally grouped according to the taxonomic order of the host. Co-infections with microfilariae and Trypanosoma spp. were also found in microscopy analyses. This study describes the presence of Hepatozoon caimani in a new host species (Paleosuchus palpebrosus) that can be a paratenic host in the natural environment. The existence of parasitic co-infections in alligator species underscores the significance of recognizing the impact of infections by various parasitic taxa on the host populations.

In this paper, we investigate the solubility effects of Co in ZnO (Zn1−xCoxO, where x = 0, 0.03, 0.05, 0.1, 0.2, 0.25, 0.4, 0.8, and 1) by combining the results of perturbed angular correlation (PAC) spectroscopy using highly diluted 111Cd as probe nuclei and ab initio calculations based on spin-density functional theory (SDFT). This combined approach enables us to characterize the local structure around Cd ions, where, through PAC technique, it was possible to measure the EFG as a function of temperature and Co concentration and thereby monitor the changes in the structure and the Co solubility threshold in ZnO and the ZnO/CoO/Co3O4 mixed phase. The full-potential linear augmented plane wave plus local orbital (APW+lo) formalism were used here to describe the electronic structure of the supercells, including the atomic relaxations. These Ab initio calculations show an interesting behavior of the Cd and Co impurity levels in the band structure of ZnO, which explains the experimental results in terms of the origin of EFG and the evidence of ferromagnetic response.

Abstract Backgrounds Observable emergence of Vancomycin-Non susceptible Coagulase-negative Staphylococci (VNS-CoNS) associated with skin and soft tissue infections spreading among the urban and rural populace is gradually intensifying severe complications. The isolated VNS-CoNS were evaluated with Matrix-assisted Laser Desorption/ionization Time of Flight Mass Spectrometry (MALDI ToF MS) for species characterization and pan-antimicrobial resistance pattern. Methods Out of 256 clinical samples collected including pus, abscess, ear swabs, eye swabs, and aspirates, 91 CoNS isolates were biotyped and further characterized with MALDI-TOF MS. Staphylococci marker genes, Vancomycin susceptibility, and biofilm assays were performed. Results Of 91 CoNS isolates, S.cohnii (2.3%), S.condimentii (3.4%), S. saprophyticus (6.7%), and S.scuri (21.1%) were characterized with MALDI-TOF with significant detection rate (99.4%; CI 95, 0.775–0.997, positive predictive values, 90.2%) compared to lower biotyping detection rate (p = 0.001). Hemolytic VNS-CoNS lacked nuc, pvl and spa genes from wound, ear, and aspirates of more 0.83 MARI clustered into a separate phylo-diverse group and were widely distributed in urban and peri-urban locations. MALDI TOF–MS yielded a high discriminatory potential of AUC-ROC score of 0.963 with true-positivity prediction. VNS-CoNS of MIC ≥ 16 µg/mL were observed among all the ages with significant resistance at 25th and 75th quartiles. More than 10.5% of CoNS expressed multi-antibiotic resistance with more than 8 µg/mL vancomycin cut-off values (p

Abstract We evaluate the accuracy of the actuator line model (ALM) approach by performing simulations for the NREL 5‐MW wind turbine in uniform inflow using three large eddy simulation codes. The power and thrust coefficients obtained using the three codes agree within 1% when the grid spacing Δgrid≤5.25 m and are cross‐validated against blade element momentum (BEM) theory. We find that the results of ALM converge towards BEM theory without the need for tip correction when the numerical resolution is increased. For Δgrid=0.98 m, the difference between the power and thrust coefficient obtained using ALM and BEM is 4.5% and 2.1%, respectively, although we note that no absolute convergence between ALM and BEM can be obtained as both models use different assumptions, such as the use of a force projection method in the ALM. The difference in the local axial and tangential forces along the blades obtained from ALM simulations using Δgrid=1.97 m and Δgrid=0.98 m can be as large as 10%. The effect of the number of actuator points on the obtained turbine power and thrust coefficients is limited as the results converge when the spacing between the actuator points is about three times the grid spacing. This insight on the required number of blade points can be used to improve the efficiency of actuator line simulations.

When houseflies find optimal conditions to develop, they rapidly increase their population size negatively impacting both humans and animals through nuisance and the transmission of pathogens. Musca domestica Linnaeus, 1758 (Diptera: Muscidae) shows a preference for animal faeces and for this reason it is a serious pest in animal breeding facilities. To prevent proliferation of houseflies and to evaluate the efficiency of the control methods, it is important to routinely monitor the activity of this dipteran in such facilities. There are several types of traps for sampling houseflies in breeding sites, here we used colored pan-traps to evaluate the efficiency of the trap and its color in sampling M. domestica in a cage poultry facility located in the city of Nepomuceno, Minas Gerais, Brazil. To do so, we set up yellow, white, blue and red pan-traps next to the cages of poultries and collected flies once a week for a period of a year. Although the density of M. domestica was high during the entire period of sampling, more flies were collected in white (monthly average of 470.83 flies) than in yellow (327.55), blue (267.14) and red traps (199.63). Hence, we argue that this poultry farm needs to improve its housefly monitoring program and we suggest a continuous use of white pan-traps to monitor the efficiency of the pest control methods implemented in the facility.

The great current challenge for the conservation and use of natural resources refers to global climate change, because of its impacts felt in different intensities at global, regional, and local spatial scales. Within the system of environmental protection areas in Brazil, the extractive reserves ensure the sustainable use of natural resources by traditional populations, thus maintaining the cultural and biological aspects of a region. Such populations, being in close management of the surrounding environments, tend to perceive changes in ecological processes that many need for their livelihoods. The use of this perception of local populations in conjunction with academic research evidence has a high potential to allow a whole and systemic view of possible changes in natural phenomena. This study developed an integrated analysis of scientific evidence and local perceptions to understand the variation of precipitation in a community inserted in an extractive reserve in the eastern Amazon. We used 30 years of precipitation data from the Brazilian National Institute of Meteorology - INMET, the Southern Oscillation Index - SOI, and the Atlantic Meridional Mode Index - AMM. Furthermore, we applied a form to measure the population's perception of possible changes in rainfall cycles in the region. The meteorological data indicate that the region of the community has been presenting a rainfall reduction; however, people in the community do not perceive this trend. Although it is public knowledge that the global climate is undergoing changes, a fact noted after the integrating analysis of scientific evidence with local knowledge in Resexmar Soure is that the perceptions of traditional populations often focus on smaller temporal and spatial scale visions.

Considering the context of the Fourth Industrial Revolution, higher education must play a significant role in the social-investment model of economic growth. To what extent higher education supports strategic academic leadership and high-tech economic development is still being determined. The article proposes direct actions for improving university management through higher educational and technological functions. We establish the specific directions for university management in neo-industrialization 4.0 to ensure extensive accessibility of higher education and enhance university management efficiency.

Davide Benedetti,1 Umberto Olcese,2 Simone Bruno,1 Marta Barsotti,3 Michelangelo Maestri Tassoni,3,4 Enrica Bonanni,3,4 Gabriele Siciliano,3,4 Ugo Faraguna1,5 1Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy; 2Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands; 3Neurological Clinics, University Hospital of Pisa, Pisa, Italy; 4Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy; 5Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, ItalyCorrespondence: Ugo Faraguna, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Via San Zeno, 31, Pisa, 56123, Italy, Tel +39 050 2213470, Email ugo.faraguna@unipi.itPurpose: A large portion of the adult population is thought to suffer from obstructive sleep apnoea syndrome (OSAS), a sleep-related breathing disorder associated with increased morbidity and mortality. International guidelines include the polysomnography and the cardiorespiratory monitoring (CRM) as diagnostic tools for OSAS, but they are unfit for a large-scale screening, given their invasiveness, high cost and lengthy process of scoring. Current screening methods are based on self-reported questionnaires that suffer from lack of objectivity. On the contrary, commercial smartbands are wearable devices capable of collecting accelerometric and photoplethysmographic data in a user-friendly and objective way. We questioned whether machine-learning (ML) classifiers trained on data collected through these wearable devices would help predict OSAS severity.Patients and Methods: Each of the patients (n = 78, mean age ± SD: 57.2 ± 12.9 years; 30 females) underwent CRM and concurrently wore a commercial wrist smartband. CRM’s traces were scored, and OSAS severity was reported as apnoea hypopnoea index (AHI). We trained three pairs of classifiers to make the following prediction: AHI < 5 vs AHI ≥ 5, AHI < 15 vs AHI ≥ 15, and AHI < 30 vs AHI ≥ 30.Results: According to the Matthews correlation coefficient (MCC), the proposed algorithms reached an overall good correlation with the ground truth (CRM) for AHI < 5 vs AHI ≥ 5 (MCC: 0.4) and AHI < 30 vs AHI ≥ 30 (MCC: 0.3) classifications. AHI < 5 vs AHI ≥ 5 and AHI < 30 vs AHI ≥ 30 classifiers’ sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV) and diagnostic odds ratio (DOR) are comparable with the STOP-Bang questionnaire, an established OSAS screening tool.Conclusion: Machine learning algorithms showed an overall good performance. Unlike questionnaires, these are based on objectively collected data. Furthermore, these commercial devices are widely distributed in the general population. The aforementioned advantages of machine-learning algorithms applied to smartbands’ data over questionnaires lead to the conclusion that they could serve a population-scale screening for OSAS.Keywords: obstructive sleep apnoea syndrome, screening, wearable devices, wrist-worn smartbands, artificial intelligence

Abstract This paper investigates international experiences and perspectives on how entrepreneurs can improve management practices while minimizing the COVID-19 pandemic’s social drama. The paper probes how companies deal with the myriad challenges they face amid the unfolding pandemic and how these processes’ economic and cultural dimensions may exert an enduring effect. A novel dataset analyses how entrepreneurs manage the change of management processes in a sample of ten countries. Three economic impacts on entrepreneurs caused by the pandemic were observed: (1) a deficit as a result of social distancing reduced due to the growth of Internet retailing; (2) a deficit resulting from a fall in demand decreased due to innovations that mitigate this demand-side change; (3) a social crisis in the labour market due to social distance and relocating many employees to remote working practices. In countries with the most considerable number of cases of COVID-19, it is recommended that attitudes towards entrepreneurial risk be raised. In countries with the vastest number of fatal cases per 100,000 people, implications for change management in entrepreneurship are an increase in Internet retailing level, a reduction in entrepreneurial fear of failure, and an increase in entrepreneurial risk awareness. Besides, an anonymous sociological survey among companies’ directors and managers in Russia on management initiatives taken on between late 2020–early 2021 shows that companies maintain a 60.21% readiness for such systemic challenges while their readiness for change increased under the influence of the pandemic. The contribution to the literature of this article lies in rethinking the COVID-19 crisis from the standpoint of social drama, which made it possible to clarify the cause-and-effect relationships of change management in entrepreneurship. For the first time, the paper proposes systemic—socio-economic recommendations for improving the practice of change management against the background of such a social drama.

This study analyses the influence of economic growth on inequality, concentrating on the role of governments as mediators. The period studied is from 2000 to 2020, encompassing 11 post-Soviet countries. The primary estimation method used is the two-stage least squares for panel data. Despite the differences in the economic and political systems at the current development stage, the post-Soviet countries share a common pattern in terms of the relationship between economic growth, the labour income share and the level of inequality, which we first show in this article. Government expenditure has the potential to reduce inequality. However, its effectiveness depends largely on government efficiency and the development of democratic institutions. Despite the increase in government spending on education, more is needed to reduce income inequality. Increased economic performance, productivity, and high-quality state institutions are necessary for this change.

Here, we discuss the effect of In2O3 nanoparticles on the reduced graphene oxide (rGO) gas-sensing potentialities. In2O3 nanoparticles were prepared with the polymer precursors method, while the nanocomposites were prepared by mixing an In2O3 nanoparticle suspension with an rGO suspension in different proportions. The gas-sensing performance of our materials was tested by exposing our materials to known concentrations of a target toxic gas in a dry airflow. Our results demonstrate that In2O3 nanoparticles enhance the rGO sensitivity for strong oxidizing species such as O3 and NO2, while a negative effect on its sensitivity for NH3 sensing is observed. Furthermore, our measurements towards H2S suggest that the concentration of In2O3 nanoparticles can induce an uncommon transition from p-type to n-type semiconductor nature when rGO–In2O3 nanocomposites operate at temperatures close to 160 °C.

Abstract We herein report a comprehensive investigation on the magnetic, structural, and electric properties of CoO nanoparticles with different sizes by local inspection through hyperfine interactions measured in a wide range of temperatures (10–670 K) by using radioactive $$^{111}$$ 111 In( $$^{111}$$ 111 Cd) tracers with the perturbed angular correlations technique. Small cobalt oxide nanoparticles with the characteristic size of 6.5 nm have been prepared by the wet chemical route that turned out to be essential to incorporate radioactivity tracers during nucleation and growth of the particles. Nanocrystalline samples with 22.1 nm size were obtained by thermal treatments under low pressure of helium at 670 K. The hyperfine data were correlated with X-ray diffraction, ZFC–FC magnetic measurements, and transmission electron microscopy to describe the structure, magnetic properties, size, and shape of samples. An analysis of the temperature evolution of hyperfine parameters revealed that the structural distortion and the magnetic disorder in the core and on the surface layer play an important role in the magnetic behavior of CoO nanoparticles.

We empirically examine the role of board gender diversity in influencing stock price crash risk at the firm-level in twelve (12) Asia-Pacific Markets. Using a dataset comprising data from 1021 listed firms over the period 2006–2016, we employ a random effect model in a regression setting. Controlling for the firm and market-level variables, we find that board gender diversity results in lowering the stock price crash risk of the firm. Bifurcating women directors on corporate board into numerical representation (token and critical mass representation), the results support our main conjectures and suggest that the economic significance of this relationship is higher for firms that have three or more women directors on the board as compared to the firms that have less than three women directors on the corporate board. Our results are robust to alternative measures of stock price crash risk, potential endogeneity and selection biases.