PirAB is a binary protein complex secreted by specific strains of Vibrio parahaemolyticus (Vp) that harbor the pVA1 virulence plasmid and express PirAVp and PirBVp toxins. PirABVp causes acute hepatopancreatic necrosis disease (AHPND), a newly emergent penaeid shrimp disease that can cause 70–100% mortality and has resulted in great economic losses since its appearance. The cy-totoxic effect of PirABVp on the epithelial cell of the shrimp hepatopancreas has been extensively reported. Our studies found that the PirBVp subunit has lectin activity and recognizes mucin-like O-glycosidic structures in the shrimp hepatopancreas. The PirAVp subunit may have a stabiliza-tion function of the binary complex. However, we also found that Vp AHPND changes the water microbiota community structure and causes a significant reduction in several bacteria, especially Neptuniibacter spp. We propose that the PirABvp toxin could exhibit a dual role: damage the shrimp hepatopancreas and kill surrounding bacteria.

A focussed library of pyridyl and 2-hydroxyphenyl chalcones were synthesized and tested for growth inhibitory activity against Mycobacterium tuberculosis H37Rv, and normal and cancer breast cell lines. Pyridyl chalcones bearing lipophilic A-ring, e.g., dichloro-phenyl- (14), pyrene-1-yl (20)- and biphenyl-4-yl (21) moieties, were found to be the most potent of the series inhibiting the growth of M. tuberculosis H37Rv with IC90 values ranging from 8.9 – 28 µM. Aryl chalcones containing a 3-methoxyphenyl A-ring and either p-Br-phenyl (25) or p-Cl- phenyl (26) B-rings showed an IC90 value of 28 μM. Aryl-chalcones were generally less toxic to HepG2 cells compared to pyridyl-chalcones. Dose-dependent antiproliferative activity against MDA468 cells was observed for trimethoxy-phenyl (16) and anthracene-9-yl (19) pyridyl-chalcones with IC50 values of 0.7 and 0.3 µM, respectively. Docking studies revealed that chalone 20 was predicted to bind to the M. tuberculosis protein tyrosine phosphatases B (PtpB) with higher affinity compared to a previously reported PtpB inhibitor.

Computational simulations of three-dimensional flow around a NACA 0018 wing with an aspect ratio of AR=5 are carried out using the Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations with the Shear-Stress Transport turbulence model closure. Simulations were performed to capture the aerodynamic stall hysteresis using a developed Pseudo-Transient Continuation (PTC) method based on a dual time step approach in the CFD code OpenFOAM. The flow was characterized by an incompressible Mach number of M=0.12 and a moderate Reynolds number Re=0.67×10^6. The results obtained indicate the presence of a noticeable aerodynamic hysteresis in the static dependencies of the force and moment coefficients, as well as the manifestation of bi-stable flow separation patterns, accompanied by the development of asymmetry in the stall zone. The URANS simulation results are in good agreement with the experimental data obtained for the NACA 0018 finite aspect ratio wing from the low-speed wind tunnel under the same test conditions. A new phenomenological bifurcation model of aerodynamic stall hysteresis under static and dynamic conditions is formulated, which is proven to be able to closely match the experimental data.

Petri nets are a graphical notation for describing a class of discrete event dynamic systems whose behaviours are charaterised by concurrency, synchronisation, mutual exclusion and conflict. They have been used over the years for the modelling of various distributed systems applications. With the advent of pervasive systems and the Internet of Things, the Calculus of Context-aware Ambients (CCA) emerged as a suitable formal notation for analysing the behaviours of these systems. In this paper, we are interested in comparing the expressive power of Petri nets to that of CCA. That is, can the class of systems represented by Petri nets be modelled in CCA? To answer this question, an algorithm is proposed that maps any Petri net onto a CCA process. We show that a Petri net and its corresponding CCA process behave the same way through experiments. It follows that CCA is at least as expressive as Petri nets, i.e. any system that can be specified in Petri nets can also be specified in CCA. Moreover, tools developed for CCA can also be used to analyse Petri nets.

The past 40 years have seen automotive Electronic Control Units (ECUs) move from being purely mechanical controlled to being primarily digital controlled. While there has been significant improvements in terms of passenger safety and vehicle efficiency including optimised fuel consumption, rising ECU numbers have resulted in increased vehicle weight, greater demands placed on power,more complex hardware and software, ad-hoc methods for updating software, and subsequent rise in costs for both vehicle manufacturer and consumer. To address these issues, the research presented in this paper proposes virtualisation technologies to be applied within automotive Electrical/Electronic (E/E) architecture. To proposed approach is evaluated through a comprehensive study of the CPU and memory resource requirement in order to support container-based ECU automotive functions. This comprehensive performance evaluation reveals that lightweight container virtualisation has the potential to welcome a paradigm shift in the E/E architecture, promoting consolidation and enhancing the architecture through power, weight and cost savings. Container based virtualisation will also enable a robust mechanism to facilitate online dynamic software updates throughout the lifetime of a vehicle.

The inherited ‘EIA’ process at Brexit is based on a ‘Project’ period from Inception tothe start of construction works. The ‘Incompleteness’ of the process covers andidentifies stages that will impact on the environmental cycle: construction period,operational life, de-commissioning and a return to acceptable environmental footprint.A master environment structure-plan framework is required to commence with theupgrading of the complete ‘EIA’ process, embracing separate limbs for the UK’spriority environmental targets for climate change, and other major adverse effectswhich result in serious ‘harm’ to the UK environment. The identification of the processfor ‘incompleteness’ requires effective sustainability, and inclusion of effectivemanagement tools, for the essential ‘monitoring/control/recording’ proceduresthroughout the project life and the natural environmental cycle. This will allow theopportunity for a new approach to a structured ‘Suite of EIAR Directives’, to enable a‘EIAR’ regime that ‘will remain fit and proper for UK purpose’.

Lifestyle has been associated with breast cancer risk through different pathways, including oxidative stress. Antioxidant enzymes are endogenous defense mechanisms against oxidative stress damage, and this response might be modulated by the genetic variation in these enzyme-codifying genes. This study aimed to analyze the synergistic effect of an antioxidant Healthy Lifestyle Index (HeLiX) composed of principal components of Western dietary pattern, alcohol consumption, smoking and physical activity, and genetic polymorphisms in the first-line antioxidant response family genes SOD, GPX, and CAT on breast cancer risk. We included 176 SNPs, and only CAT rs554576 remained significant after correction for multiple comparisons. Breast cancer odds were reduced at the highest (T3) and medium (T2) tertiles of the HeLiX. When stratified by HeLiX, we observed a reduced risk of breast cancer with at least one T-allele, and the effect increased in a dose-dependent manner. Compared to the reference category (HeLiX T1 and AA genotype), women at the HeLiX T3 with AT and TT genotypes in postmenopausal women showed an OR = 0.15 (95% CI 0.07–0.32). For HeLiX T2 and AT genotype OR = 0.26 (95% CI 0.13–0.54); for TT genotype OR = 0.24 (95% CI 0.12–0.45). For premenopausal women, at the HeLiX T3 and AT genotype OR = 0.29 (95% CI 0.13–0.62); for the TT genotype OR = 0.21 (95% CI 0.08–0.51). We also observed an inverse association for HeLiX T2 and TT genotype (OR 0.39 95% CI 0.17–0.87). Our study shows a significant synergistic gene-environment interaction on an additive scale, contributing to understanding pathways involved in breast cancer etiology and prevention.

Nuclear DNA mutations, mitochondrial DNA mutations, combined nuclear and mitochondrial DNA defects, and random occurrences are the main causes of mitochondrial disease. Black pigmentation loss is a major sign of Parkinsonism. Because of the loss of dopaminergic neurons in the substantia nigra, it drops to less than 80%. The degree of motor impairment was correlated with the amount of black pigmentation loss. After RNA extraction, reverse transcription is carried out because reverse transcriptase was used to create cDNA. One microliter of total RNA supplemented with IORT Buffer, dNTPs, random hexamers, Multi-Scribe Reverse Transcriptase, and nuclease-free was used to create cDNA. The following was how the reaction was carried out in a thermal cycler: 10 minutes at 25°C, 120 minutes at 37°C, 5 seconds at 85°C, and lastly 4°C. The data was expressed as a v-value, which shows how much the target gene is enriched in comparison to the reference gene. Earlier research using mice injected with functional HtrA2/Omi protease activity revealed similar outcomes, including induced up-regulation of CHOP, decreased mitochondrial function, and early brain cell aging because of an increase in mtDNA deletions. The cell viability of the genotypes exhibits a dmg concentration-dependent effect in these results, suggesting that high content ratios of drug treatment with 6-OHDA may be the cause of cellular content depletion. After 6-OHDA neurotoxin treatment, CHOP is up-regulated. Prior in vitro research has shown that treatment with a model based on 6-OHDA neurotoxin causes the activation of mitochondrial stress pathways, which in turn promotes the death of neurons. 6-OHDA reversibly inhibited complexes I and IV's activities in rat brain cells, which led to dopaminergic neurodegeneration, a defining feature of PD pathogens. As a result, the number of living cells will directly correlate with the dmg concentration, supporting the results of the current study. Real-time PCR can generally demonstrate that the removal of HtrA 2 results in a significant up-regulation of Hsp60 expression when compared to WT cells. This could be linked to a decreased threshold for mitochondrial stress in HtrA2 KO cells, which would explain why, following ADEP4 and ACP5 treatment, Hsp60 is significantly up-regulated in HtrA2 KO cells compared to WT cells.

Popular, industry, and academic attention is increasingly being paid to Electrically-Assisted Pedal Cycles (EAPCs), also known as electric bikes, or e-bikes. Attention has also begun to be given to ideas of the electric bicycle as a component of “electric velomobility” or “e-velomobility” and to the particular benefits of electric bicycles over conventional bicycles. We present here the effects of EAPCs on the tangible quantitative levels of greenhouse gas emission reductions, increased mobility performance, and greater accessibility of cycling; and the intangible qualitative level of perceptions of electric cycling and those who engage in it, harmonized with transhumanist lines of thought in order to articulate a sociotechnical imaginary of the electric bicycle as an augmentation to a cyclist’s physical body. Through a combination of original research and drawing on prior literature, we articulate the idea of a “cyborg cyclist” as a vision for present and future e-velomobilities, and emphasize the ability of appropriate technology to augment the capabilities of cyclists, viewing rider and machine as a single unit, while also warning of the possible risks of inappropriate types of electric bicycle. Such a view, we believe, adds a much-needed technology-positive view to present debates, and highlights especially the ability of the EAPC as a rehabilitative and augmentative mobility tool, and as a means of displacing more carbon-intensive means of transportation, particularly the private car.

This study aimed to characterize the risk of falling in low, moderate and high risk participants from two different geographical locations using a portable force-plate. A sample of 390 older adults from South and North America were matched for age, sex, height and weight. All participants performed a standardized balance assessment using a force plate. Participants were classified in low, moderate and high risk of falling. No differences were observed between South and North American men, nor comparing North American men and women. South American women showed the significantly shorter center of pressure path length compared to other groups. The majority of the sample was categorized as having low risk of falling (male: 65.69 % and female: 61.87 %), with no differences between men and women. Also, no differences were found between North vs. South Americans, nor for falls risk levels when male and female groups were compared separately. In conclusion, South American women had better balance compatible with the status of the 50-59 years’ normative age-range. The prevalence of low falls risk was ~ 61-65 % and the prevalence of moderate to high risk was ~ 16-19 %. The frequency of fall risk did not differ significantly between North and South Americans, nor between males and females.

Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease that affects the nervous system. Peripheral blood leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNA-CN) are potential biomarkers of disability and neurological damage. The present work evaluated LTL and mtDNA-CN in 75 relapsing-remittent MS (RRMS) patients 50 of whom had an Expanded Disability Status Scale (EDSS) 0 to 3 (mild-moderate disability), and 25 had an EDSS of 3.5 to 7 (severe disability). Absolute LTL and absolute mtDNA-CN were measured via real-time polymerase chain reaction (qPCR). The LTL and mtDNA-CN were significantly lower in RRMS severe disability than in RRMS mild-moderate disability (3.924 ± 0.124 vs 2.854 ± 0.092, p<00001; 75.14 ± 1.77 vs 68.06 ± 1.608, p<0.00001, respectively). The LTL and mtDNA-CN showed a linear correlation in RRMS with mild-moderate disability (r=0.2986, p=0.0351). In addition, in a binary logistic regression model the LTL can predict severe disability (AUC=0.697, p=0.0031, cutoff ≤ 3.0875 Kb, sensitivity= 73.1%, specificity=62.5%), the prediction is improved by including age to the model (AUC=0.765, <0.0001, sensitivity=78.26%, specificity=81.25%). Aging is closely linked to the development of disability in RRMS and can be evaluated through LTL and mtDNA-CN absolute quantification.

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

Studies have demonstrated the critical role that safety plays in preserving favourable working conditions in the construction industry, which is necessary to accomplish goals. The aim of this research was to inform stakeholders in the construction industry in developing nations about the value of safety and possible strategies for influencing their opinions regarding safety protocols. The importance of safety to the construction sector, which is crucial to the advancement of the country, has also been emphasized. However, due to a lack of adequate safety understanding among stakeholders in the construction sector, the construction industry is characterized by a great deal of instability and hazard. To determine what factors, affect productive working conditions in the construction production, this study examined safety. A conceptual framework for safe working conditions in the construction sector was developed by considering several aspects, including the person dimension, environment factor, safety behaviour, organization features, technology, and incentives. It is now imperative to bring in these dimensions to improve the safe working conditions in the construction industry, particularly in the developing countries. By putting these safety factors into practice, the construction industry can reduce safety risks, lower the number of accidents and fatalities, cut expenses related to subpar safety performance, safeguard the reputation of construction companies, boost employee morale and satisfaction with their work, enhanced employee retention, reduced absenteeism, and enhanced sustainability goals. Additionally, the proposed conceptual framework is assured to be new and to be widely accepted in the developing nations. Based on this assumption the conceptual framework is designed.

As global concerns about climate change intensify, the need for effective strategies to reduce carbon emissions has never been more urgent. This paper explores the crucial role of data automation (DA) and decision support systems (DSS) in enhancing decarbonation efforts within the realms of solid waste management (SWM), wastewater treatment (WWT), and contaminated soil remediation (CSR). Specifically, the paper provides: (i) an overview of the carbon footprint (CFP) in relation to environmental management (EM) and the role of DA and DSS in decarbonization; (ii) DA case studies in areas of SWM, WWT, and CSR; (iii) 3. life cycle assessment (LCA) based DSS case studies in areas of SWM, WWT, and CSR; (iv) multi-criteria decision analysis (MCDA) based DSS case studies in areas of SWM, WWT, and CSR; and (v) optimal contractual delivery methods based DSS case studies in EM practices. The analysis disclosed that adoption of DA and DSS in SWM, WWT, and CSR holds significant potential for decarbonizing these EM processes. By optimizing operations, enhancing resource efficiency, and integrating renewable energy sources, these technologies contribute to the reduction of GHG emissions and promote sustainable environmental practices. As the demand for more effective and eco-friendly solutions grows, the role of DA and DSS will become increasingly pivotal in achieving global decarbonization goals.

The use of unmanned aerial aircrafts (UAVs) is governed by strict regulatory frameworks that prioritize safety. To guarantee safety, it is necessary to acquire and maintain situational awareness (SA) throughout the operation. Existing Canadian regulations require pilots to operate their aircrafts in visual line-of-sight. Therefore, the task of acquiring and maintaining SA primary falls to the pilots. However, the development of aerial transport is entering a new era with the adoption of a highly dynamic and complex system known as advanced air mobility (AAM), which involves UAV operating autonomously beyond visual line-of-sight. SA must therefore be acquired and maintained primarily by each UAV through specific technologies and procedures. In this paper, we review these technologies and procedures in order to decompose the SA of the UAV in the AAM. We then use the system modeling language to provide a high-level structural and behavioral representation of the AAM as a system having UAV as its main entity. In a case study, we analyze one of the flagships UAVs of our industrial partner. Results show that this UAV doesn’t have all the technologies and methodologies necessary to achieve all the identified SA goals identified for the safety of the AAM. This work is a theoretical framework intended to contribute to the realization of the AAM, and we also expect to impact the future design and utilization of UAVs.

Breast cancer (BC) affects millions of women; it is the leading cause of death by neoplasia in wom-en worldwide, with at least 500 thousand deaths each year, 70% of which occur in developing countries. Elastography evaluates tissue stiffness, making this a promising non-invasive real-time technique. BI-RADS is recognized as a standard and helpful technique for establishing BC risk. This study aimed to determine, by strain elastography (SE), the fat-to-lesion index (F/L index), sen-sitivity, specificity, and optimal cut-off to diagnose BC. This prospective study included 216 wom-en who underwent SE, ultrasound, mammography, and breast biopsy; according to mammogra-phy, we recruited BI-RADS category 2 (n= 5), category 3 (n=29), category 4 (n= 94), category 5 (n= 71) and category 6 (n=17); after biopsy, 108 women were classified as negative, and 108 were pos-itive for BC. Three expert BC radiologists performed all imaging interpretations and biopsies. Our results show mean values of the F/L index for negative biopsies of 3.70±2.57 and positive biopsies of 18.10±17.01; we developed two models for the prediction of BC, a logistic regression model with an AUC of 0.893 and a neural network with an AUC of 0.902. The Youden index yielded a F/L index cut-off >5.76, with a sensitivity and specificity of 84.26%. Positive Spearman's Rho cor-relation coefficient was observed between the F/L index and BI-RADS, r=.073 (p< 0.001). ANOVA test showed a difference between F/L index vs. molecular subtypes (p=0.002). SE is helpful as a di-agnostic complement to mammography, or in cases where the latter is contraindicated, elas-tography has an adequate predictive capacity and is a fast and minimally invasive procedure.

Background: This paper examined the gap between obesity and its diagnosis for cohorts of patients with overweight, obesity, and morbid obesity in the Veterans Administration (VA) population. Using the risk adjustment models, it also identified factors associated with the underdiagnosis of obesity. Methods: Analysis was performed on a VA data set. We identified diagnosed patients and undiag-nosed patients (identified through BMI but not diagnosed by ICD-10 codes). The groups’ de-mographics were compared using nonparametric chi-square tests. We used logistic regression analysis to predict the likelihood of the omission of diagnosis. Results: Of the 2,900,067 veterans with excess weight, 46% were overweight, 46% had obesity, and 8% of them had morbid obesity. The overweight patients were the most underdiagnosed (96%), followed by the obese (75%) and morbidly obese cohorts (69%). Older, male, and White patients were more likely to be undiagnosed as overweight and obese; younger males were more likely to be undiagnosed as morbidly obese. (p<.05) Comorbidities significantly contributed to diagnosis. Conclusion: Underdiagnosis of obesity continues to be a significant problem despite its prevalence. Diagnosing obesity accurately is necessary to provide effective management and treatment.

Bio-economy is a major area of the strategy that can afford the European Union to achieve growth: (i) smart, through the development of knowledge and innovation; and (ii) sustainable, based on a greener, more efficient economy in resource management. We believe that the progress of bio-economy cannot be achieved without the harnessing of intellectual capital. Our research aimed to emphasize the benefits of the dynamics of the intellectual capital growth on the evolution of the bio-economy. Thus, the information published by Eurostat (European Statistic Institute) during a period spanning seven years (2011-2018) was used to assess the influence exerted by the conduct of the harness of intellectual capital related to sustainability as well as for the reporting of indicators relevant to appreciating an economic progress and sustainability (renewable waste material, share of renewable energy and energy intensity of the economy). The ultimate goal was represented by the generation of a regression model to see what factor influences mostly the progress of the bio-economy at European and Romanian level. Significant dependency relationships were identified. The results remain robust even after the introduction of certain control variables, such as gross domestic product rate, food production, population growth, urbanization growth and inflation. Our paper sets out to contribute to expanding the specialty literature by highlighting the involvement of intellectual capital as a factor in optimizing sustainability growth and, at a methodological level, by using a multiple regression.

The use of video in education has become ubiquitous as technological developments have markedly improved the ability and facility to create, deliver and view videos. The concomitant pedagogical transformation has created a sense of urgency regarding how video may be used to advance learning. Initial reviews have suggested only limited potential for the use of video in higher education. More recently, a systematic review of studies on the effect of video use on learning in higher education, published in the prestigious Review of Educational Research, found, overall, effects to be positive. In the present paper we critique this study and provide some needed clarity to the state of research on learning via video in higher education. We reveal significant gaps in the study methodology and write-up and use a cognitive processing lens to critically assess and reanalyse study data. We found results of this study to be only applicable to learning requiring lower-level cognitive processing and conclude, consistent with prior research, learning benefits remain limited.

Air pollution includes particle-bound Polycyclic Aromatic hydrocarbons (PAHs) which eventually reach the placenta triggering adverse perinatal outcomes by long-term exposure. Late-ly, air pollution has increased over the Metropolitan Area of Medellin-Colombia (MAMC) but its effects on pregnancy are still unknown. In this research, we made a real-time analysis of airborne total PAHs using a photoelectric sensor for residential places influenced by industrial and traffic sources contrasting southern and northern MAMC during the second peak of the bimodal ten-dency for PM2.5 emissions in this region. Additionally, we analyzed individual PAHs by GC/MS coupled to pressurized hot water extraction methodology. Data was applied in an Inhalation In-take Model to assess pregnancy exposure. The average concentration of PAHs over southern MAMC was three times higher than over northern MAMC where the abortion rate has been 1.4 times higher presented in database. Previous research found that PAHs act as an Endo-crine-Disrupting Chemical (EDC) during pregnancy and even heavy congeners could reside in umbilical cord blood. Finally, the annual series of abortion rates in the MAMC showed a signifi-cant correlation with the annual average levels of PM2.5 which are associate to PAHs. Although this significant correlation does not imply causality, our results suggest an important connection between both variables. This latter finding opens a gap in deeply understanding how regions with high PAHs-convergence influences abortion rates in MAMC.

The study aims to explain the different effects between the multiplication, addition, division and subtraction equations. In this sense, multiplication and addition equations develop a new element or fact, meanwhile, division equations express information within the element or fact, subtraction is the selection of element or fact. Furthermore, for a multiplication and addition equation results in the new element or fact, it is necessary to depend on specific physical concepts, without extreme alteration, as it would result in the alteration of the element or fact. It is worth highlighting the importance of fixed values ​​in the equation to describe the specific nature of the element or fact. The study makes it possible to understand open equations (without solutions) in mathematics and physics, in addition to understanding existing equations. The study makes reference to the theory of obligatory necessity and the theory of differences between elements.

O estudo apresenta uma afirmação e explicação de que ocorrem progressões numéricas maiores e menores que dependem da representação contida no espaço físico. Em casos gerais, números maiores são múltiplos e números menores são simples, porque vários números contêm mais números em muitos espaços físicos do que números simples. Em casos específicos, dependem da afirmação do que é a representação específica, podendo ocorrer realidades diferentes de casos gerais. Além disso, a teoria explica a mudança no número de números primos.

Biofilm formation is important in the free-living and symbiotic lifestyles of Sinorhizobium meliloti. Here we show that the S. meliloti NspS-MbaA system is homologous to the c-di-GMP modulating NspS-MbaA system described in Vibrio cholerae and modulates biofilm formation, exopolysaccharide (EPS) production and motility in S. meliloti in response to exogenous polyamines. Biofilm and EPS production in quorum sensing-deficient wild type strain 1021 decreased in cultures containing putrescine, 1,3-diaminopropane or spermine, but were unaffected in a 1021 nspS mutant (1021 nspS). Decreases in biofilm formation caused by these polyamines paralleled decreases in EPS production and increases in nspS transcription. Cell aggregation did not differ markedly between strain 1021 and 1021 nspS. The S. meliloti quorum sensing-proficient Rm8530 wild type strain and nspS mutant (Rm8530 nspS) produced similar levels of biofilm under control conditions and 3.2- and 2.2-fold more biofilm in cultures with norspermidine, but these changes did not correlate with EPS production. Rm8530 nspS aggregated up to several fold more than the wild type under most conditions. Changes caused by polyamines in swimming and swarming motility were not generally dependent on NspS-MbaA in either 1021 or Rm8530. We speculate that the S. meliloti NspS-MbaA system could modulate biofilm formation in response to environmental polyamines.

Bio-economy is a major area of the strategy that must enable the European Union to achieve growth: smart, through the development of knowledge and innovation; and sustainable, based on a greener, more efficient economy in resource management. We believe that the progress of bio-economy cannot be achieved without the harnessing of intellectual capital. Our research aimed to emphasize the benefits of the dynamics of the intellectual capital growth on the evolution of the bio-economy. The aim of this analysis was to study the established link between the Energy Intensity of the Economy (EIE) and a number of factors that can measure the intellectual capital, such as: Market Capitalization of Bitcoin, Patent applications listed by European Patent Office and the Turnover from Innovation as a proportion of the total Turnover. The ultimate goal was represented by the generation of a regression model to see what factor influences mostly the progress of the bio-economy at European and Romanian level.

The theory says that the first things to exist in the universe and the current moment were driven by an imperative need; that is, the intensities of the physical concept specify influence the existence of elements and facts based on the countless observations in physical spaces in relation to elements and facts. The existence of mandatory elements in space is motivated by the characteristics of the spaces that offer conditions for such an obligation. The theory states that the universe did not arise by chance; that is, the universe emerged through determination influenced by its surroundings. The objective of the study is to help explain the elements and facts of the universe from its origins to the present.

The development of reliable predictive algorithm for house price as the housing market is a stand-out among the most involved regarding valuing the price and continues to fluctuate, is constantly a need for socio-economic advancement and welfare of citizen. In this paper, we develop machine learning algorithms for forecasting UK housing Price, and find an optimal algorithm that forecasts housing price accurately on the premises of the presence of many features or covariates. After applying correlation analysis to remove correlated variables in order to avoid multicollinearity, thereby increasing the statistical power, a novel method of using regression analysis to first of all understand and select statistically significant features for the various regions in England based on North South divide is adopted. These features are then used in the machine learning algorithm to further increase the statistical power of the algorithm, increase the level of accuracy for each of them and ultimately increase the predictive values for the algorithms. The model construction involves 3 stages: 1- correlation analysis to identify and remove correlated variables thereby avoiding multicollinearity and increasing the statistical power of the linear regression, 2 - using linear regression to determine variables that are statistically significant and 3 - building the machine learning algorithms based on the variables that are statistically significant from the linear regression. A comprehensive dataset of UK Paid housing Price from 2010 to 2019 was linked to a number of other datasets to generate a total 21 variables or features used for the models. Catboost, Gradient Boosting, Bagging, Random Forest, Extra Tree all achieved the excellent models performance result in all the regions considered. The comparison of the seven models showed that Extra Tree algorithm consistently achieved the best performance in term of level of accuracy in all the regions. K-Nearest Neighbours (KNN) is the only algorithm with less than 50% level of accuracy. Noticeably, the regions considered had varying or differing insignificant variables, implying that although many variables are common (statistically significant) to all the regions, there are regional differences and impact when modelling or predicting housing prices. This study validates the practicability of developing a machine learning methodology for the prediction of housing price. This research offers a reference for future house price prediction based on machine learning.

The antioxidant, antimicrobial, antiproliferative, and enzyme inhibitory properties of five extracts from aerial parts of Salvia pachyphylla were examined to assess the prospective of this plant as a source of natural products with therapeutic potential. Those properties were analyzed performing a set of standard assays. The extract obtained with dichloromethane showed the most variety of components, as yielded promising results in all completed assays. Furthermore, the extract obtained with ethyl acetate exhibited that greatest antioxidant activity as well as the best xanthine oxidase inhibitory activity. Remarkably, both extracts obtained with n-hexane or dichloromethane revealed significant antimicrobial activity against the Gram-positive bacteria; also, they showed greater antiproliferative activity against three representative cell lines of the most common types of cancers in women worldwide, and against a cell line that exemplifies cancers that typically develop drug resistance. Despite that other extracts were less active, such as the methanolic or aqueous, their results are promising for the isolation and identification of novel bioactive molecules.

The Theory of differences between elements explains the reasons for the differences in physical concepts between different elements, such as quantum physics and the Theory of general relativity, being explained through observations. Thus, it is possible to conclude from the observations that the differences are motivated by the reactions between the elements, by the composition of the elements, and by the influence of the spaces that promote losses and gains of characteristics; therefore, there is no general similarity between quantum physics and the general Theory of relativity. The study aims to understand the elements and their physical concepts that make up the Universe.

Aims: This systematic review aims to evaluate the influence of Environmental Enrichment (EE) on oncological factors in experimental studies involving various types of cancer models. Methods: A comprehensive search was conducted in three databases: PubMed (161 articles), Embase (335 articles), and Scopus (274 articles). Eligibility criteria were applied based on the PICOS strategy to minimize bias. Two independent researchers performed the searches, with a third participant resolving any discrepancies. The selected articles were analyzed, and data regarding sample characteristics and EE protocols were extracted. The outcomes focused solely on cancer and tumor-related parameters, including cancer type, description of the cancer model, angiogenesis, tumor occurrence, volume, weight, mice with tumors, and tumor inhibition rate. Key-findings: A total of 770 articles were identified across the three databases, with 12 studies meeting the inclusion criteria for this systematic review. The findings demonstrated that different EE protocols were effective in significantly reducing various aspects of tumor growth and development, such as angiogenesis, volume, weight, and the number of mice with tumors. Furthermore, EE enhanced the rate of tumor inhibition in mouse cancer models. Findings: This systematic review highlights the significant impact of EE protocols on multiple parameters associated with tumor growth and development, including angiogenesis, occurrence, volume, weight, and tumor incidence. Moreover, EE demonstrated the potential to increase the rate of tumor inhibition. These findings underscore the importance of EE as a valuable tool in the management of cancer.

Forecasting streamflow accurately is essential to achieve an efficient integrated water resources management strategy and provide consistent support to water decision-makers. We present a simple, low-cost and robust approach for forecasting monthly and yearly streamflow during the hydrological year in course, applicable to headwater catchments. It combines the use of regression analysis techniques, the two-parameter Gamma continuous cumulative probability distribution function and the Monte Carlo method. It is based on a probabilistic comparison of the progression of the current hydrological year with the historic observed series. The methodology has been successfully applied to two headwater reservoirs within the Guadalquivir River Basin in southern Spain. The root-mean-square error and correlation coefficient were used to measure the accuracy of the model and the results showed good levels of reliability. The outputs are the probabilistic monthly and yearly streamflow and 80% confidence interval. Further reductions in prediction errors may be achieved from increasing the number of observed years. These risk-based predictions are of great value, especially, before the intensive irrigation campaign starts (usually in April), when Water Authorities are to take responsible management decisions about the best allocation of the available water volume between the different water users and environmental needs.

This article presents an in-depth review of Virtual Power Plant (VPP), its organization in the energy system and its prospects in the face of the promising future of the increasing bidirectional complexity exposed in the current scenario. A new paradigm for the operations of modern power distribution and transmission systems requires greater grid flexibility that is accompanying an extensive change in the structure of electricity markets, the fruit of the development of the renewable industry and of the growing photovoltaic systems popularized, but in contrast due to the intermittent nature cause variable uncertainties in the power system. Innovative concepts like VPP are becoming a reality, establishing an efficient and effective mechanism. The objectives and components are described in a comprehensive way, and some of the most important are pointed out and presented in detail to contribute with a description of the energy systems and the implicit research needed for sustainability and resilience in the eminent energy scenario with this technology. In addition, the literature and studies of this technology already indicate a direction of this new tool as a promising solution to manage the uncertainties of the renewable energies.

Retailers must have accurate sales forecasts to operate their businesses efficiently and effectively and to remain competitive in the marketplace. Global forecasting models like RNNs can be a powerful tool for forecasting in retail settings, where multiple time series are often interrelated and influenced by a variety of external factors. By including covariates in a forecasting model, we can better capture the various factors that can influence sales in a retail setting. This can help improve the accuracy of our forecasts and enable better decision-making for inventory management, purchasing, and other operational decisions. In this study we investigate how the accuracy of global forecasting models is affected by the inclusion of different potential demand covariates. To ensure the significance of the study's findings, we used the M5 forecasting competition's openly accessible and well-established dataset. The results obtained from the DeepAR models, which were trained on various combinations of features including time, price, events, and IDs, suggest that individually only the features corresponding to IDs improve the baseline model. However, when all the features are used together, the best performance is achieved, indicating that the individual relevance of each feature is emphasized when the information is given jointly. Comparing the model with features to the model without features, there is an improvement of 1.76\% for MRMSSE and 6.47\% for MMASE.

Background: Hospital accreditation has become ubiquitous in developing countries. Although studies recognize that accreditation can improve healthcare quality, efficiency, and safety, there are doubts about how hospitals deal with conflicts caused by the different institutional logics that inhabit this process. Therefore, this study aimed to investigate how professional and market logics, as well as the conflict between institutional demands, affect compliance with hospital accreditation. Methods: To this end, we developed a multiple case study in four Brazilian hospitals through in-depth interviews with sixteen participants (managers, physicians, nurses, physiotherapist) and on-site observation by the triangulation between the analysis of the narratives and the results of the multiple correspondence analysis. The interpretation and subsequent categorization of the interviews were guided by the study's analytical categories: institutional logics (professional and market); adoption objectives (legitimacy and efficiency); strategic responses to adoption (conformity, non-conformity, and customization); nature of demands (origin in the means and in goal). Results. The data showed that when professional logic is prominent, there is a greater tendency to customize activities, as there are conflicts in the means by which activities can be developed. When market logic stands out, there is a risk of non-conformity, mainly because the focus falls exclusively on goals. Finally, the data point to the absence of conflicts between justifications related to efficiency and legitimacy. Conclusion. We conclude the study by highlighting the theoretical and practical implications of recognizing the conflict between logics, contributing to a deeper understanding of how logic influences the attention given to specific demands and, more significantly, how they affect compliance with hospital accreditation standards, expanding the body of knowledge in the area.

Recent advancements in artificial intelligence (AI) and deep learning have revolutionized the field of protein engineering, particularly in the area of de novo protein design. This review article explores the impact of AI-driven approaches on protein design, with a specific focus on the role of structure prediction neural networks, such as AlphaFold and RoseTTAFold. The article discusses the paradigm shift brought about by these networks, which have enabled the design of proteins with unique structures and functions that are not found in nature. The review covers various aspects of AI-driven protein design, including the use of protein language models to harness evolutionary information, the development of de novo protein design workflows utilizing deep learning, and the application of generative models like RFdiffusion and RoseTTAFold All-Atom. The article also highlights the successes and applications of AI-driven protein design across diverse domains, such as enzyme engineering, antibody design, and vaccine development. Additionally, the review identifies current challenges and future directions in the field, emphasizing the need to address limitations in modeling conformational dynamics and designing proteins for in vivo functionality. The article concludes by underscoring the potential of AI-driven protein design to transform various aspects of science and technology, while also acknowledging the importance of interdisciplinary collaboration and the development of robust pipelines for the validation and optimization of designed proteins. Overall, this comprehensive review serves as a valuable resource for researchers and practitioners interested in understanding the current state and future prospects of AI-driven protein design.

Nasal polyposis is defined by a Th2-driven chronic inflammation of the nose and sinus with polyps visible in the nasal fossae. It is a prevalent disease with a significant impact on the HRQL. Allergy, allergic rhinitis, asthma, and aspirin intolerance are frequently associated. The management is individual. The first line of treatment is a long-term treatment with intranasal corticosteroids. Oral corticosteroids should be used with caution. When the medical treatment fails the patient is eligible for sinus surgery. In case of symptomatic recurrence after both medical treatment and ethmoidectomy, biologics are nowadays a very promising treatment effective on all the respiratory tract. Dupilumab seems in the literature the molecule of choice. However, besides the international guidelines published by EPOS and Euforea, the molecule prescribed depends also on the availability of it in each country and the criteria edited by the health authorities to get reimbursement. Long treatment is mandatory. Traditional medical treatment is necessary as a complement to biologics.

The effect of initial immunosuppressive therapy on the kinetics of the SARS-CoV-2 vaccine-induced humoral response is unknown. Here, we compared the kinetics of SARS-CoV-2 vaccine-induced humoral response in chronic kidney disease patients undergoing kidney transplantation (KTRs) and compared to patients remaining on dialysis during the Omicron circulation. This prospective, non-randomized, real-world study included 113 KTRs and 108 patients on dialysis. Those with previous COVID-19 or negative IgG at screening were excluded. Blood samples were collected to assess SARS-CoV-2 IgG titers and neutralizing antibodies at months (M) 1, 3, 6, and 12. Seroreversion occurred in 1 KTR and in 3 patients on dialysis. KTRs had lower IgG titers over time (M1: 10,809.3±12,621.7 vs. 15,267.8±16,096.2 IU/mL; M3: 12,215.5±12,885.8 vs. 15,016.2±15,346.1 IU/mL; M6: 12,540.4±13,010.7 vs. 18,503.5±14,581.0 IU/mL; p=0.005), but Neutralizing antibodies were similar (M1: 94.0 vs. 90.3%; M3: 92.9 vs. 90.5%; M6: 99.0 vs. 95.5%; M12: 98.9 vs. 97.5%; p=0.812). During follow-up, KTRs received more vaccine (141 vs. 73; p<0,001) and had more COVID-19 (32.7% vs. 14.8%; p=0.002). Compared to patients on dialysis, KTRs had lower SARS-CoV-2 IgG titers and similar rates of seroreversion and neutralizing antibodies over time. Although KTRs received more boosters, they had a higher incidence of COVID-19.

The signature of chaotic systems can be characterized either by the sensitivity of the initial conditions or by the change of its parameters. This feature can be used for manufacturing high sensitivity sensors. Sensors based on chaotic circuits have already been used for measuring water salinity, inductive effects, and both noise and weak signals. This article investigates an impedance sensor based on the Van der Pol and Duffing damped oscillators. The calibration process is a key point and therefore the folding behavior of signal periods was also explored. A sensitivity of 0.15 kΩ/Period was estimated over a range from 89.5 to 91.6 kΩ. This range can be adjusted according to the application by varying the gain of the operational amplifier used in this implementation. The development of this type of sensor might be used in medical and biological engineering for skin impedance measurements, for example. This type of chaotic sensor has the advantage of sensing small disturbances and then detect small impedance changes within biological materials which, in turn, may not be possible with other detectors.

The present study explored whether exposure to complex childhood trauma (CCT) is reflected in the resting-state electroencephalography (EEG) temporal alpha power of complex trauma-exposed adolescents, given the association of temporal alpha with fear circuitry (learning and conditioning) in a sample of 25 adolescents and similar controls, ages 12-17 years. Both trauma and psychopathology were screened or assessed, and resting-state EEG was recorded, following a preregistered protocol for data collection. Temporal alpha power, corresponding to T5 and T6 electrode location (10-20 international system), was extracted from resting-state EEG in both eyes-open and eyes-closed conditions. We found that in the eyes-open condition, right, but not left, temporal alpha was significantly higher in adolescents exposed to CCT, relative to healthy controls, suggesting that childhood trauma exposure may have a measurable impact on alpha oscillatory patterns, specifically in the right temporal region. Our study highlights the importance of considering neural markers, such as temporal alpha power, in understanding the long-term consequences of CCT exposure in developmental samples, with possible important clinical implications in guiding neuroregulation interventions.

The main objective of this study was to study the effect of occupational stress on turnover intentions, as well as whether this relationship is mediated by burnout levels and moderated by motivation. The sample of this study consisted of 603 participants, all employees of the Portuguese Tax and Customs Authority, which is part of the Ministry of Finance and belongs to the Direct State Administration. The results indicate that occupational stress (with managers, with career and remuneration and with work overload) has a positive and significant effect on turnover intentions and that this relationship is mediated by burnout. Motivation (intrinsic and identified) has a negative and significant effect on turnover intentions. Intrinsic motivation moderates the rela-tionship between occupational stress (with managers, with colleagues, with career and pay and with family problems) and turnover intentions. These results indicate that among the dimensions of occupational stress, the most critical are stress with managers, work overload and career and pay. These are factors that the Direct State Administration should be concerned about in trying to minimize their causes.

Introduction: OS2966 is a fist-in-class, humanized and de-immunized monoclonal antibody which targets the adhesion receptor subunit, CD29/β1 integrin. CD29 expression is highly upregulated in glioblastoma and has been shown to drive tumor progression, invasion, and resistance to multiple modalities of therapy. Here, we present a novel Phase I clinical trial design addressing several factors plaguing effective treatment of high-grade gliomas (HGG). Study Design: This 2-part, ascending-dose, Phase I clinical trial will enroll patients with recurrent/progressive HGG requiring a clinically-indicated resection. In Study Part 1, patients will undergo stereotactic tumor biopsy followed by placement of a purpose-built catheter which will be used for intratumoral, convection-enhanced delivery (CED) of OS2966. Subsequently, patients will undergo their clinically-indicated tumor resection followed by CED of OS2966 to the surrounding tumor-infiltrated brain. Matched pre- and post-infusion tumor specimens will be utilized for biomarker development and validation of target engagement by receptor occupancy. Dose escalation will be achieved using a unique concentration-based accelerated titration design. Discussion: The present study design leverages multiple innovations including: 1) the latest CED technology, 2) 2-part design including neoadjuvant intratumoral administration, 3) a first-in-class investigational therapeutic, and 4) concentration-based dosing. Trial registration: A U.S. Food and Drug Administration (FDA) Investigational New Drug application (IND) for the above protocol is now active. A Phase I trial is registered at clinicialtrials.gov (NCT04608812).

The theory says that number interacts with spaces based on the meaning of mathematics, in this way it is possible to obtain numerical knowledge. The theory shows the possibility of using spaces related to each other to efficiently discover whether results and origins are even or odd, but always applying rules to make this work. the study uses equivalent representations of odd and even numbers. Thus, it is possible to discover the possibilities of origins and their results.

The theory of limited numbers says that the number is not infinite, that is, the number is limited in parts or completely. To reach a conclusion about the limited number, one must understand the meaning of mathematics and varied spaces, therefore, one must understand that mathematics and spaces interact. Mathematics has the function of describing the world precisely, where numbers represent elements or facts that rationally belong to space, and spaces have different intensities of specific physical concepts in each space; therefore, there is no infinite element or fact due to differences in the intensities of specific physical concepts in spaces that do not allow for the fact or fact in all spaces.

Vaginal ecosystem is a unique environment where, in physiological conditions, lactobacilli dominate. However, also pathogenic microbial species, responsible of vaginitis and vaginosis, can harbor vaginal microbiota. To extend the data published by De Seta and Larsen in Pathogens (2021), here we analyzed both the anti-Candida and anti-inflammatory properties of the vaginal gel formulation, Respecta® Balance Gel (RBG), commercialized as an adjuvant to treat vaginitis and vaginosis. We evaluated its activity by an in vitro model where a monolayer of A-431 vaginal epithelial cells was infected by Candida albicans in the presence of RBG or the placebo formulation (pRBG). Specifically, we tested the RBG capacity to counteract C. albicans virulence factors as well as their anti-inflammatory properties. Our results show that, unlike the placebo, RBG reduces ,reduces, C. albicans adhesion, its capacity to form hyphae and C. albicans-induced vaginal cell damage. Interestingly, both RBG and pRBG reduce LPS-induced IL-8 secretion (being RBG the most effective) demonstrating that also the placebo retains anti-inflammatory properties. By our experimental approach we highlight the possible role of farnesol on such effects, but we would like to point out that lactic acid, polydextrose and glycogen too must be relevant in the actual application. Taken together, our results show that RBG impairs C. albicans virulence and is able to reduce the inflammation in the vaginal environment, ultimately allowing the establishment of a balanced vaginal ecosystem.

In a context of increasingly necessary energy transition, precise modelling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSO) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modelling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow the estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating degree-day (HDD), the cooling degree-day (CDD) and the HDD+CDD were computed from an ensemble of 7 high-resolution bias-corrected simulations attained from EURO-CORDEX under RCP4.5 and RCP8.5. These three indicators were analyzed for 1971-2000 (from E-OBS) and 2011-2040 and 2041-2070, under both RCPs. Results show that the overall spatial distribution of HDD trends for the 3 time-periods points out an increase of energy demand to heat internal environments in Portugal's northern-eastern regions, most significant under RCP8.5. It is projected an increase of CDD values for both scenarios; however, statistically significant linear trends were only found for 2041-2070 under RCP4.5. The need for cooling is almost negligible for the remaining periods, though linear trend values are still considerably higher for 2041-2070 under RCP8.5. By the end of 2070, higher amplitudes for all indicators are depicted for southern Algarve and Alentejo regions, mainly under RCP8.5. For 2041-2070 the Centre and Alentejo (North and Centre) regions present major positive differences for HDD(CDD) under RCP4.5(RCP8.5), within the 5 NUTS II regions predicting higher heating(cooling) requirements for some locations.

Background: Multidrug-resistant bacteria present resistance mechanisms against β-lactam antibiotics, such as Extended-Spectrum Beta-lactamases (ESBL) and Metallo-β-lactamases enzymes (MBLs) operon encoded in Gram-negative species. Likewise, Gram-positive bacteria have evolved other mechanisms through mec genes, which encode modified penicillin-binding proteins (PBP2). This study aimed to determine the presence and spread of β-lactam antibiotic resistance genes and the microbiome circulating in Quito’s Public Transport (QTP). Methods: A total of 29 station turnstiles were swabbed to extract the surface environmental DNA. PCRs were performed to detect the presence of 13 antibiotic resistance genes and to identify 16S rDNA barcoding, followed by clone analysis, Sanger sequencing and BLAST search. Results: ESBL genes blaTEM-1 and blaCTX-M-1 and MBL genes blaOXA-181 and mecA were detected along QPT stations. Two subvariants were found for blaTEM-1, blaCTX-M-1, and blaOXA-181. Almost half of the circulating bacteria found at QPT stations were common human microbiota species including those classified by the WHO as pathogens of critical and high-priority surveillance. Conclusions: β-lactam antibiotic resistance genes are widely spread throughout QPT. This is the first report of blaOXA-181 in environmental samples in Ecuador. Moreover, we detected a new putative variant of this gene. Some commensal coagulase-negative bacteria may have a role as mecA resistance reservoirs

Socially Responsible Investments, also referred to as ethical or sustainable investments, have experienced rapid global growth in recent years. They represent an investment approach that incorporates social, environmental, and ethical considerations into decision-making processes. Consequently, the significance of SRIs has captured the attention of academics, prompting inquiries into the impact of integrating social criteria on portfolio performance. The primary objective of this work was to conduct a comparative study of the performance between socially responsible and non-socially responsible investment funds, using funds domiciled in Portugal and Spain. Various multi-factor models, including the three-factor model of Fama and French (1992), the four-factor model of Carhart (1997), and the five-factor model of Fama and French (2015), were employed to assess performance. The sample comprised 125 investment funds, with 43 identified as socially responsible and 82 as non-socially responsible. The study's findings indicate that there are no significant differences between socially responsible funds and their conventional counterparts. The majority of funds experience performance alterations during periods of crisis compared to crisis-free periods. Additionally, when comparing non-conditional models with conditional models, an improvement in the explanatory power of the latter is observed. This suggests that the inclusion of the dummy variable enhances the quality of fit for the models.

Knee osteoarthritis (KO) is an important health condition, affecting one third of the people aged 65 years or more. Pain is the main cause of disability. Pain management in KO includes pharmacological and non-pharmacological modalities. Patient education, lifestyle changes, physical exercise and physical agents are prescribed as a first approach for pain control. Laser therapy is part of many therapeutical protocols, with two forms, low-level laser therapy (LLLT) and high-intensity laser therapy (HILT). The paper aimed at stressing the advantages of HILT, based on a greater wavelength, higher energy delivery and deeper tissue penetration. Research on 23 published trials revealed that analgesic effect is rapid, cumulative and long lasting. Compared to sham, to LLLT or to other associations of therapeutical modalities, HILT provided significantly better results on pain reduction and functional improvement. Ultrasound examination showed reduction of intraarticular inflammation.

Modern building automation systems implement plenty of advanced control and monitoring functions considering various parameters like users’ activity, lighting, temperature changes etc. Moreover, new solutions based on Internet of Things and cloud services are also being developed for smart buildings to ensure comfort of use, user safety, energy efficiency improvements and integration with smart grids and smart city platforms. Such a wide spectrum of technologies and functions requires a new approach in building automation systems design to provide effective way of their implementation and flexibility during operation. At the same time, in the building design and operation industries, tools based on building information modeling and digital twins are being developed. In this paper, the authors discuss development directions and application areas of these solutions, identifying new trends and possibilities of their use in smart homes and buildings. In particular, the focus is on procedures for selecting automation functions, effective integration, and interoperability of building management systems with Internet of Things considering organization of prediction mechanisms and dynamic functional changes in buildings and smart networks. Chosen solutions and functions should consider the requirements from EN ISO 52120 standard and the guidelines defined for the Smart Readiness Indicator.

This study presents an in-depth analysis and evaluation of self-healing networks as an innovative solution to combat the escalating threat of ransomware attacks. Recognizing the limitations of traditional network security methods in the face of advanced cyber threats, the research focuses on the development and implementation of self-healing networks, characterized by their dynamic, intelligent response systems. Utilizing a combination of artificial intelligence and machine learning algorithms, these networks demonstrate remarkable adaptability and resilience. Through rigorous simulations, the study examines the efficacy of self-healing networks in detecting, isolating, and recovering from ransomware attacks, with an emphasis on their ability to learn and evolve from each incident. The research highlights the strengths and limitations of these networks and discusses their potential applications in various sectors. The findings suggest that self-healing networks, with their proactive and adaptive defense mechanisms, represent a significant advancement in cybersecurity strategies, offering a robust solution against a range of cyber threats. Future work is recommended to further enhance the capabilities of self-healing networks, particularly in the areas of speed, detection accuracy, and quantum-resistant security measures.

This research looks into the evolving dynamics of ransomware, shifting from conventional encryption-based attacks to sophisticated data exfiltration strategies. Employing the Bidirectional Encoder Representations from Transformers (BERT) model, the study analyzes network traffic patterns to detect ransomware activities, offering new insights into their covert operations. The findings emphasize the need for advanced AI tools in cybersecurity, highlighting the significance of adapting and innovating defense strategies to counter the changing landscape of ransomware threats. The study contributes to a deeper understanding of ransomware evolution and underscores the importance of integrating AI in cybersecurity practices.

With the integration of small unmanned aircraft systems into the U.S. National Airspace System, low altitude regions are being stressed in historically new ways. The FAA must understand and quantify the risk of collision between unmanned and manned aircraft during desired low altitude unmanned operations in order to produce regulations and standards. It is increasingly important to characterize how manned aircraft operate at these low altitudes, as historical assumptions are insufficient for modeling and simulation to support standards development. Yet technical challenges such as poor low altitude radar coverage and lack of required transponder equipage are significant barriers to characterizing the low altitude environment. In response, we conducted an extensive review of fixedwing and rotary-helicopter manned operations to characterize the low altitude environment.

We report a modification of the freeform reversible embedding of suspended hydrogels (FRESH) 3D printing method for the fabrication of freeform perfusable microfluidics inside a hydrogel matrix. Xanthan gum is deposited into a CaCl2 infused gelatin slurry to form filaments, which are consequently rinsed to produce hollow channels. This provides a simple method for rapid prototyping of microfluidic devices based on biopolymers and potentially a new approach to the construction of vascular grafts for tissue engineering.

This paper aims to contribute to the advancement of scientific knowledge about the impact of the COVID-19 pandemic on social workers and the social work profession in Romania. Research has shown that social work is a profession at high risk for developing the burnout syndrome, which has many detrimental effects on both social workers and the clients that they serve. Two conceptual models are used to frame the discussion: the theoretical framework of VUCA (volatility, uncer-tainty, complexity, and ambiguity) to discuss the challenges of the unprecedented context the COVID-19 pandemic has created for social workers; stress and burnout to explain the negative impact of this period of time. Based on convergent mixt methods, the study sample consisted of 83 social workers employed in statutory and private social services in Romania, from different fields of intervention. Results show that 25,3% of respondents suffer from a high level of burnout and 44.6% scored in a range that indicate a medium level of burnout. A group of 31.1% have managed to handle stress factors in a healthy manner. Main stressors found are especially personal (fear of contamination, personal and family) and work-related factors (workload, new legislative rules and decisions, inconsistency, instability, ambiguity of managerial decisions, or even their absence or non-assumption, lack of clarity of working procedures, limited managerial and supervisory support, limited financial resources), less than client related factors (lack of direct contact, risk of contami-nation in two ways, managing beneficiaries fears, difficulties related to technology and digital skills). Study results point to the importance of organizational support and developing a self-care plan that help protect against occupational stress and burnout. Recommendations are made putting forward the voice of fieldworkers and managers fostering initiatives and applications of sustainability-based measures and activities designed to deal with the challenges of the VUCA environment.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

Background: Chronic lateral epicondylitis challenges the therapeutical approach; underlying mechanisms are incompletely understood; neuropathic pain and central and peripheral sensitization may explain the fact that botulinum toxin was found to play a role in pain and function management. Methods: We searched the literature for MeSH terms: lateral epicondylitis or synonyms and botulinum toxin. Results: We found 14 papers containing trials on botulinum toxin injection into the tendon or into the extensor muscles (particularly extensor carpi radialis brevis and extensor communis digitorum). We followed the administration pathways, doses, timing and side effects. Conclusion: With chronic course, the focus of the therapy shifts from the afflicted tendon to the inserting muscles, as muscle contracture may create a vicious loop to perpetuate and aggravate the disease. Doses, timing and side effects are discussed.

The main purpose of this work is to contribute to understanding the mechanism of oxidation of the polymeric components of common disposable masks used during the COVID-19 pandemic to offer the chemical basis to predict their long-term behaviour under typical environmental conditions. Artificial ageing of representative mask layers under isothermal conditions (110℃) or accelerated photoageing showed that all the PP-made components underwent a fast oxidation process, following the typical hydrocarbon oxidation mechanism. In particular, yellowing and the melting temperature drop are early indicators of their diffusion-limited oxidation. Morphology changes also induced a loss of mechanical properties, observable as embrittlement of the fabric fibres. Results were validated through preliminary outdoor ageing of masks, which allows us to predict they will suffer fast and extensive oxidation only in the case of contemporary exposure to sunlight and relatively high environmental temperature, leading to their extensive breakdown in the form of microfiber fragments, i.e., microplastics.

Quambalaria eucalypti is a fungal pathogen that causes leaf spot, shoot blight, and stem canker disease in Eucalyptus spp. Although the advanced stages of the disease show clear symptoms, diagnosis of the early stages can be challenging. To enable fast and sensitive screening of asymptomatic or latent infected plant material for Q. eucalypti, a specific SYBR green-based real-time PCR assay targeting the partial histone-H3 region was developed. The assay was demonstrated to be specific for Q. eucalypti and did not give cross-reactivity with any of the other Quambalaria species examined or other eucalyptus pathogens. The primers developed in this study ensured high analytical sensitivity, allowing the detection of Q. eucalypti DNA concentrations as low as 10 fg DNA from asymptomatic plants. Comparable results were obtained in interlaboratory testing, demonstrating the assay's robustness and effectiveness in other laboratories. This newly developed quantitative PCR assay can be used for more comprehensive epidemiological investigations, testing plant material in known Q. eucalypti distribution areas for early management strategies, or collecting data for resistance breeding programs.

Research professors develop scientific products that impact and benefit society, but their competencies in doing so are rarely evaluated. Therefore, employing a mixed two-stage sequential design, this study developed a self-assessment model of research professors’ competencies with four domains, seven competencies, and 30 competency elements. Next, we conducted descriptive statistical analysis of those elements. In the first year, 320 respondents rated themselves on four levels: initial, basic, autonomous, and consolidated. In the assessment model’s second year, we compared 30 respondents’ results with those of their initial self-assessment. The main developmental challenge was Originality and Innovation, which remained at the initial level. Both Training of Researchers and Transformation of Society were at the basic level, and Digital Competency was at the autonomous level. Both Teaching Competence and Ethics and Citizenship attained the consolidated level. This information helps establish priorities for accelerating researchers’ training and the quality of their research.

This paper presents the experimental campaign conducted near the Condoroma dam at 4075 m a.s.l. in an experimental setup consisting of a series of standard profile spillways with a vertical upstream face of up to five different dimensionless heights (P/Hd). The experimental results indicate that for all P/Hd ratios studied, the discharge coefficients adjusted to the Condoroma altitude are lower than those reported by classical formulations used in conventional spillway design. As a result, a generalized equation is proposed to estimate the discharge coefficient for standard spillways located in dams at similar elevations above sea level.

Sudden unexpected death (SUD) is a fatal event that occurs in an apparently healthy subject so that such an abrupt outcome could have not been predicted. SUD - including sudden intrauterine unexplained death (SIUD), sudden neonatal unexpected death (SNUD), sudden infant death syndrome (SIDS), sudden unexpected death of the young (SUDY), sudden unexpected death in the adult (SUDA) - occurs as the first manifestation of an unknown underlying disease or within a few hours of presentation of a disease. SUD is a major unsolved, shocking form of death that occurs frequently and can happen at any time without warning. For each case of SUD, a review of clinical history data and performance of a complete autopsy, particularly focused on the study of the cardiac conduction system were carried out according to the necropsy protocol devised by the Lino Rossi Research Center, Università degli Studi di Milano, Italy. Research cases are represented by 75 SUD victims, subdivided into 15 SIUD, 15 SNUD, 15 SUDY, and 15 SUDA victims, collected and selected for this study. After the routine autopsy and clinical history analysis, the death remained unexplained and hence a diagnosis of SUD was assigned to the 75. subjects, which included45 females (60%) and 30 (40%) males, ranging in age from 27 gestational weeks to 76 years. Serial sections of the cardiac conduction system disclosed frequent congenital alterations, of the cardiac conduction system in fetuses and infants. An age-related significant difference in distribution among the 5 age-related groups was detected for the following anomalies of the conduction system: central fibrous body (CFB) islands of conduction tissue, fetal dispersion, resorptive degeneration, Mahaim fiber, CFB cartilaginous meta-hyperplasia, His bundle septation, sino-atrial node (SAN) artery fibromuscular thickening, atrio-ventricular junction hypoplasia, intramural right bundle branch, and SAN hypoplasia. The results data are useful to understand the cause of death for all SUD cases that were unexpected and would have otherwise remained unexplained, so to motivate medical examiners and pathologists to perform more in-depth studies.

Global models have been developed to tackle the challenge of forecasting sets of series that are related or share similarities, but not for heterogeneous datasets. Various methods of partitioning by relatedness have been introduced to enhance the similarities of the set, resulting in improved forecasting accuracy but often at the cost of a reduced sample size, which could be harmful. To shed light on how the relatedness between series impacts the effectiveness of global models in real-world demand forecasting problems we perform an extensive empirical study using the M5 competition dataset. We examined cross-learning scenarios driven by the product hierarchy commonly employed in retail planning, which allow global models to capture interdependencies across products and regions more effectively. Our findings show that global models outperform state-of-the-art local benchmarks by a considerable margin, indicating that they are not inherently more limited than local models and can handle unrelated time series data effectively. The accuracy of data partitioning approaches increases, as the size of the data pools and the models' complexity decrease. However, there is a trade-off between data availability and data relatedness. Smaller data pools lead to increased similarity among time series, making it easier to capture cross-product and cross-region dependencies, but this comes at the cost of a reduced sample, which may not be beneficial. Finally, it's worth noting that the successful implementation of global models for heterogeneous datasets can significantly impact forecasting practice.

Unmanned Aerial Vehicles (UAVs) in particular multirotors are becoming the {\it de facto} tool for aerial sensing and remote inspection. In large industrial facilities, a UAV can transmit an online video stream to inspect difficult to access structures, such chimneys, deposits and towers. However, the communication range is limited, constraining the UAV operation range. This limitation can be overcome with relaying UAVs placed between the source UAV and the control station, creating a line of communication links. In this work we assume the use of a digital data packet network technology, namely WiFi, and tackle the problem of defining the exact placement for the relaying UAVs that creates an end-to-end channel with maximal delivery of data packets. We consider asymmetric communication links and we show an increase as large as $15$\% in end-to-end packet delivery ratio when compared to an equidistant placement. We also discuss the deployment of such a network and propose a fully distributed method that converges to the global optimal relay positions taking, on average, 1.4 the time taken by a centralized method.

Plant-based proteins, like those derived from hemp and rapeseed can significantly contribute to a balanced diet and human daily nutritional requirements by providing essential nutrients such as protein, fiber, vitamins, minerals, and antioxidants. According to numerous recent research papers the consumption of plant-based proteins has been associated with numerous health benefits, including reduced risk of chronic diseases such as heart disease, diabetes, and certain cancers. Plant-based diets are often lower in saturated fat and cholesterol and higher in fiber and phytonutrients, which can support overall health and well-being. Present research investigates the nutritional attributes, functional properties, and potential food applications of hemp and rapeseed protein for a potential use in new food product development, with a certain focus on identifying anti-nutritional factors and bioactive compounds. Through comprehensive analysis, anti-nutritional factors and bioactive compounds were elucidated, shedding light on their impact on protein quality and digestibility. The study also delves into the functional properties of hemp and rapeseed protein, unveiling their versatility in various food applications. Insights from this research contribute to a deeper understanding of the nutritional value and functional potential of hemp and rapeseed protein, paving the way for their further utilization in innovative food products with enhanced nutritional value and notable health benefits.

An ongoing EU Horizon 2020 Project called BionicVEST is investigating the effect of constant electrical stimulation (ES) of the inferior vestibular nerve in patients with bilateral vestibular dysfunction (BVD)[1]. The evidence is that constant ES results in improved postural stability and gait performance and so the question of central importance is how could constant ES of mainly saccular afferents in these BVD patients cause this improved performance? We suggest that the constant ES is substituting for the absent saccular neural input to the vestibular nuclei and the cerebellum in these BVD patients and indirectly via these structures to other structures which have been of great recent interest in motor control. One target area, the anterior midline cerebellum (the uvula) has recently been targeted as a location for deep brain stimulation in human patients to improve postural stability and gait. There are projections from midline cerebellum to basal ganglia including the striatum, structures involved in the initiation of gait. It may be that the effect of this activation of peripheral saccular afferent neurons is analogous to the effect of deep brain stimulation (DBS) by electrodes in basal ganglia acting to help alleviate the symptoms of patients with Parkinson's disease.

Currently, companies and SMEs (small and medium enterprises) are looking to be more competitive. In order to achieve this, they are adopting new business models and strategies that allow them to move towards sustainability. Strategies such as CSR (Corporate social responsibility) and supply chain management have become essential for ensuring a company’s permanence and financial consolidation. The literature has stated that the theories of Stakeholders and Sustainability are fundamental pillars for the development and sustained growth of business. The purpose of this article is to examine the effects of CSR and the SC (supply chain) on innovation, image and reputation, and in turn, their influences on profitability in SMEs. This research is based on a sample of 143 companies in the city of Guaymas Sonora, in Mexico. For the analysis and validation of the results, we used the SEM (Structural Equation Modeling) statistical technique based on the variance, through PLS (Partial Least Squares) (using SmartPLS version 3.2.6 Professional). The findings show that SMEs that develop social and sustainable practices increase their level of innovation, and improve their image, their reputation, and their financial profitability. This work contributes mainly to the development of Stakeholders and Sustainability.

Health differences across socioeconomic strata have always pointed out that poorer and minorities have higher mortality and morbidity than richer and majorities. This difference is exacerbated for particular populations such as the victims of ongoing armed conflicts, who are also much harder to quantify due to the conflict itself. This study applies network analysis to a combination of three large administrative records for the health system and mortality records in the province of Risaralda (Colombia) between 2011 and 2016. It produces the most common causes of morbi-mortality for both victims of violence and the poorest inhabitants of Risaralda, defined as those who qualify as recipients of subsidies from the Colombian welfare program called SISBEN in the categories of highest need. Both populations show high morbidity frequencies for non-communicable diseases such as Type II diabetes, hypertension, and hyperglyceridaemia, mostly associated with exposure to unhealthy lifestyles. Additionally, the mortality outcomes reflect the different lifestyles and medical treatments of both subpopulations. While the poorest replicate the same causes identified for morbidity, the victims of armed conflict die of additional causes including Type II diabetes, which reflects the even worse conditions they face.

Guava (Psidium guajava L.) is a species is widely distributed in Córdoba, despite this, there are few studies that have been carried out to understand its genetic diversity. For this reason, the objective of this research was to evaluate the genetic diversity and variability of guava (Psidium guajava L) using microsatellite markers in Montería, Córdoba-Colombia. Forty-five accessions were evaluated. For DNA extraction, the CTAB 2x extraction protocol was used with modifications. The extracted DNA was amplified by the PCR technique using seven microsatellite markers. A total of 46 alleles were found with an average of 6.5 alleles per locus. A total of 28 private alleles were identified in the populations, possibly fixed by different evolutionary forces. The evaluated population presented an average expected heterozygosity of 0.572 and the observed heterozygosity was lower (0.058). The fixation index presented a total average of 0.906, indicating that in Montería there is an excess of homozygotes. The PIC values allowed us to determine that the markers mPgCIR9, mPgCIR11, mPgCIR13, mPgCIR16, mPgCIR19 and mPgCIR22 are highly informative, while mPgCIR23 is moderately informative. The guava population in Montería presented a low genetic diversity within the subpopulations, which could be related to inbreeding events such as self-pollination..

PM2.5 levels affect human health. However, its relationship with other health vulnerability determinants has not been sufficiently explored. Furthermore, public access to PM2.5 datasets, linkable to health statistics, is not available. We built a georeferenced database and map of annual mean PM2.5 emissions and air concentrations values in Argentina in 2010 and explored their correlations with other health vulnerability determinants. We obtained data for montlhy PM2.5 values emissions and air concentrations in Argentina from public sources. We evaluated health vulnerability by the “Sanitary Vulnerability Index (SVI)”. Non-parametric correlations between variables below 0.22, corresponding to a R2=5%, were deemed meaningless. PM2.5 emissions concentrated in urban and intensive agricultural areas of Argentina. PM2.5 air concentrations were acceptable (≤10 microg/m3) in only 15% of the Argentinean territory, respectively. The correlation between air concentration of PM2.5 and human emission was meaningless. Emissions, but not air concentrations correlated &gt;0.22 with indicators of human activity. SVI correlated meaninglessly with PM2.5 air concentration. In conclusion, PM2.5 levels were above acceptable levels in 85% of the Argentinian territory in 2010. The lack of meaningful correlations between PM2.5 and SVI suggest that these coefficients might be used in combination to assess health vulnerability. Further research is warranted.

this article presents the results of implementing existing software tools in the accounting field. The teaching processes regarding the use of Learning and Knowledge Technologies (TAC) in the university environment, and very specifically, in what has to do with the pedagogical integration of the same in the curriculum is deficient and disjointed with the current technological development. Thus, in the different curricula of professional programs of Public Accounting and related, the courses related to computer automation processes are oriented only towards the management of computer science and accounting software and the great diversity of existing applications that would undoubtedly directly benefit the student to know the potential of these in their future accounting practice is not taken into account. Strengthen the various skills of a Public Accountant in training through Learning and Knowledge Technologies (TAC), under the hypothesis of developing skills in the accounting field through TACs. The research was developed using a quantitative approach, an empirical-analytical method, with a type of descriptive research under an experimental design based on G1 x O1 and G2–O2, three phases were defined. In the first phase, the characterization of the existing software tools in the accounting field was carried out. In the second phase, their relevance was determined. In the third phase, performance was evaluated and then classified in a repository. The data obtained were analyzed with parametric analysis techniques through which it was found that the difference in quantitative results in the academic process between the experimental and control groups was statistically significant, which concluded the success of the experimental treatment. The use of CT scans in the classroom by the experimental group resulted in an improvement in their academic performance compared to the control group, strengthening their self-learning processes and facilitating the development of cognitive functions and skills necessary in the exercise of their accounting profession. This research supports and strengthens the work skills developed in the classroom for public accounting students. The tools TAC is developed from the request made by the radiometry laboratory as a first phase and a second phase is necessary for validation with experts.

The anthropometric features offer an overall image of the nutritional status. The investigated groups were aged 19 and 21. The anthropometric measurements of height and weight were recorded following standard procedures. The objectives of this study were to evaluate the harmonious body development, the nutrition status and the body composition. The evolution of the stature increases until 20 years after which stagnation follows. The body mass index of subjects was found to be normal. The body fat may vary over time in subjects depending on age and gender. Body water and body muscle mass content increased with age. The harmony of body development was assessed by means of the Amar index. Regarding the constitutional index, the women subjects belong to the leptosome type and the male subjects belong to the picnic type. The status of the investigated subjects is within the average stature.

The postpartum period is marked by profound changes in women at a physical, psychological, and physiological level. Many of these changes persist after four to six weeks postpartum, and most women do not resume their levels of physical activity, which increases the risk of remaining inactive for many years. It is crucial to implement effective programs that promote exercise during the postpartum period. The objective of this study was to test the feasibility and analyze the effects of a structured and supervised postpartum exercise program on the maternal health and fitness parameters. To analyze the potential effects of the intervention, the level of physical activity, quality of life, pelvic girdle and low back pain, fatigue, depression, and the level of functional and physical fitness were assessed at baseline, after 8 weeks, and after 16 weeks of intervention. Feedback on the exercise program was collected after the final assessment. The results showed that a structured and supervised postpartum exercise program was feasible and safe, and produced positive effects on selected maternal health and fitness parameters. These results will encourage a study protocol with a larger sample in order to prove its effectiveness, improve the guidelines for postpartum exercise, and incorporate this program into a routine health care setting.

In recent years there has been increasing interest in the discovery of new natural herbal remedies for the treatment of common conditions such as diabetes and inflammatory diseases. In this context, this paper analyzed the antidiabetic and anti-inflammatory potential of two plants of the genus Artemisia: Artemisia absinthium (wormwood) and Artemisia vulgaris (mugwort) and Trigonella foenum-graecum (fenugreek) plants less studied from this point of view. Thus, hydroal-coholic extracts (50% EtOH v/v, 10% mass) were made, which were processed by membrane technologies, micro- and ultrafiltration, in order to concentrate the biologically active principles. The extracts were then analyzed in terms of content in active principles of interest (polyphenols, flavones). The antidiabetic activity of the extracts was analyzed by testing their ability to inhibit α-amylase and α-glucosidase and the anti-inflammatory activity by testing the ability to inhibit hyaluronidase (HYA) and lipoxygenase (LOX). Thus, the T. foenum-graecum extracts showed a high inhibitory activity on α-amylase 3.22 ± 0.3 g / mL (compared to the standard used - IC50 acarbose = 3.5 g / mL) and a high inhibitory activity on LOX: 19.69 ± 0.52 g/mL (compared to all standards used). The concentrated extract of Artemisia vulgaris showed increased activity of inhibition of α-amylase - IC50 = 8.57 ± 2.31g/mL and moderate activity of inhibition of HYA - IC50 = 17.18 g/mL compared to ibuprofen, the standard used - IC50 = 5.73 g/mL. The concentrated extract of Artemisia absinthium showed a pronounced activity of inhibition of LOX - IC50 = 19.71 g / mL, compared to the standard - rutin - IC50 = 22.34 g/mL).

In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.

HIV/AIDS infection increases vulnerability to ill-health states and has a major impact on the general health status. This study aims to describe Angolan adolescents and adults’ comprehensive knowledge of HIV/AIDS and its associated factors based on the 2016 demographic and health survey (DHS). Data from 19,785 individuals between the ages of 15 and 49 years old, who re-sponded to all the DHS questions between October 2015 and March 2016 were included in this study. Multivariable analysis using logistic regression was used to compute the adjusted odds ratio and respective 95% confidence intervals. In Angola, 47.7% of the respondents had general com-prehensive knowledge of HIV/AIDS. The odds of having comprehensive knowledge about HIV/AIDS were higher among individuals who watch television (aOR: 2.40; 95% CI: 2.11, 2.72) or read journals and magazines (aOR: 1.99; 95% CI: 1.72, 2.30) more than once a week and, people with primary or higher-level education (aOR: 1.83; 95% CI: 1.67, 2.00). Similarly, for people living in urban areas (aOR: 1.51; 95% CI: 1.34, 1.71). These results may reflect important inequities and can assist decision-makers in advocating to continue to invest in health literacy for HIV but also in the development of tailored interventions in this area.

Secure attachment, developed through consistent relationships with attachment figures in childhood, is a crucial factor in fostering healthy interpersonal relationships and a positive self-perception. This research aimed to assess how perceived security, as an indicator of secure attachment, predicts adult self-concept through the mediating effects of resilience and positive self-esteem. A quantitative, cross-sectional, and non-probabilistic study was conducted with 383 participants, of whom 76.2% were females, aged between 17 and 86 years (M = 28.52, SD = 12.23). Correlational analyses revealed significant positive associations between perceived security, self-concept, resilience, and positive self-esteem. Path analysis demonstrated that resilience and positive self-esteem sequentially mediate the relationship between perceived security during childhood and adult self-concept (Total Effect R2 = .34, F(1,381) = 193, p < .001; Indirect effect of sequential mediation b = .02, CI 95% [.01, .04]). Findings suggest that the ability to cope with ad-versity and personal acceptance underlie the impact of perceived security on self-concept. It is recommended to promote not only secure attachment in family interventions but also resilience and self-esteem in programs targeting adolescents, youth, and adults.

In the bioprinting process, controlling the motion of bioprinters involves a computer-aided design (CAD) model, converting that model into g-code, and transmitting the motion commands to the bioprinters. The g-code file contains information about the motion of the axes and can be generated using various software. However, a challenge arises when using g-code between different bioprinters. Therefore, the objective of this study was to propose a reliable method for analyzing the differences in 3D bioprinting devices by parameterizing a crucial variable for extrusion bioprinting: the E-value. Four bioprinters from three different manufacturers were used to investigate the extrusion behavior when subjected to the same E-value.

Background: Gingival enlargement is defined as an abnormal overgrowth of gingival tissues. A case of a 34–year–old female presenting with maxillary chronic inflammatory gingival enlargement associated with a nickel wire allergy is reported here. Replacement of the wire, good oral hygiene therapy and surgical therapy was carried out to provide a good aesthetic outcome. Histopathological evaluation was done of the excised specimen. There is only one similar case reported in literature to the best of our knowledge and ours is the second case. Result: A Histopathological diagnosis of inflammatory fibrous hyperplasia was established. No recurrence was reported at the end of 1 year. Conclusion: The patient should be made aware of the allergy at the initial visit and oral hygiene instructions should be reinforced at every visit. The significance of patient compliance during and following therapy as an important factor in the success of treatment.

Whole-genome sequencing has advanced our understanding of the population structure of the pathogenic species complex Cryptococcus gattii, which has allowed for the phylogenomic specification of previously described major molecular type groupings and novel lineages. Recently, isolates collected in Mexico in the 1960s were determined to be genetically distant from other known molecular types and were classified as VGVI. We sequenced four clinical isolates and one veterinary isolate collected in the southwestern U.S. and Argentina during 2012-2021. Phylogenomic analysis groups these genomes with those of the Mexican VGVI isolates, expanding VGVI into a clade and establishing this molecular type as a clinically important population. These findings also potentially expand the known Cryptococcus ecological range with a previously unrecognized endemic area.

Vimentin is an intermediate filament protein that plays key roles in integration of cytoskeletal functions, and therefore in basic cellular processes such as cell division and migration. Consequently, vimentin has complex implications in pathophysiology. Vimentin is required for a proper immune response, but it can also act as an autoantigen in autoimmune diseases or as a damage signal. Although vimentin is a predominantly cytoplasmic protein, it can also appear at extracellular locations, either in a secreted form or at the surface of numerous cell types, often in relation to cell activation, inflammation, injury or senescence. Cell surface targeting of vimentin appears to associate with the occurrence of certain posttranslational modifications, such as phosphorylation and/or oxidative damage. At the cell surface, vimentin can act as a receptor for bacterial and viral pathogens. Indeed, vimentin has been shown to play important roles in virus attachment and entry of severe acute respiratory syndrome-related coronavirus (SARS-CoV), dengue and encephalitis viruses, among others. Moreover, the presence of vimentin in specific virus-targeted cells and its induction by proinflammatory cytokines and tissue damage contribute to its implication in viral infection. Here, we recapitulate some of the pathophysiological implications of vimentin, including the involvement of cell surface vimentin in interaction with pathogens, with a special focus on its role as a cellular receptor or co-receptor for viruses. In addition, we provide a perspective on approaches to target vimentin, including antibodies or chemical agents that could modulate these interactions to potentially interfere with viral pathogenesis, which could be useful when multi-target antiviral strategies are needed .

Proprotein convertases activate various envelope glycoproteins and participate in cellular entry of many viruses. We recently showed that the convertase furin is critical for the infectivity of SARS-CoV-2. This study investigated the implication of the two cholesterol-regulating convertases SKI-1 and PCSK9 in SARS-CoV-2 entry. We used cell-to-cell fusion assays in HeLa cells and pseudoparticle entry into Calu-3 cells. SKI-1 increases cell-to-cell fusion by enhancing the activation of SREBP-2, whereas PCSK9 reduces cell-to-cell fusion by promoting the cellular degradation of ACE2. Metalloprotease activation is sensitive to enhanced cholesterol levels resulting from SKI-1-activated SREBP-2 that leads to enhanced S2’ formation. However, high metalloprotease activity results in S2’ shedding into a new C-terminal fragment (S2”), leading to reduced cell-to-cell fusion. Indeed, S-mutants that increase S2’’ formation, abolish S2’ and cell-to-cell fusion, as well as pseudoparticles entry, indicating that the formation of S2’’ prevents SARS-CoV-2 cell-to-cell fusion and entry. We next demonstrated that PCSK9 enhanced the cellular degradation of ACE2, thereby reducing cell-to-cell fusion. However, different from the LDLR, a canonical target of PCSK9, the C-terminal CHRD domain of PCSK9 is dispensable for the PCSK9-induced degradation of ACE2. Molecular modeling suggested binding of ACE2 to the Pro/Catalytic domains of mature PCSK9. Thus, both cholesterol-regulating convertases SKI-1 and PCSK9 can modulate SARS-CoV-2 entry via two independent mechanisms.

The discharge of industrial effluents containing toxic heavy metals in water sources has serious consequences for human health and the environment, and biosorption appears to be an environmental-friendly and cost-effective alternative that can be used for wastewater treatment. The use of different types of agricultural waste as biosorbents for the removal of toxic heavy metals, although an alternative, is quite difficult to apply in practice because these wastes have many other uses. Based on these considerations, in this study, soybean biomass (SB), soybean waste biomass obtained from oil extraction (SBW) and biochar obtained from soybean waste pyrolysis (BC-SBW) were testes as biosorbents form the removal of Pb(II) and Cd(II) ions, in batch systems. Under optimal conditions (pH = 5.4, 4.0 g biosorbent/L, room temperature (25 ± 1 C), contact time = 180 min), the biosorption capacity increase in the order: SB &lt; SBW &lt; BC-SBW for both metal ions, indicating that BC-SBW has the highest efficiency in removing toxic heavy metals. In addition, experiments on wastewater samples have shown that, in addition to significant reducing the content of heavy metals, BC-SBW also significant improved other quality indicators (such as: pH, TSM, CCO-Cr, CBO5), compared to the other biosorbents (SB and SBW). Quantitative evaluation of the biosorptive performance of each biosorbent (SB, SBW and BC-SBW) shows that BC-SBW has a real chance of being used on an industrial scale for wastewater treatment. All these aspects allowed the development of a circular approach for the use of soybean biomass in the removal processes of toxic heavy metals. This approach minimizes the shortcomings of using biomass as a biosorbent and increase the chance of using these materials in industrial practice.

The objective of the study was to apply the principles of analytical quality by design (AQbD) to the analytical method for the determination of the radiochemical purity (PQR) of the radiopharmaceutical sodium iodide 131I oral solution, by means of thin layer chromatography (TLC) with a Radio-TLC scanner, the same one that allows to evaluate the quality of the product. For the AQbD, the analytical objective profile (ATP), critical quality attributes (CQA), risk management, the method operable design region (MODR) were defined through the response surface methodology for method optimization using the MINITAB ® software, Control Strategy and the validation of the method where the parameters of selectivity, linearity, precision, robustness, detection limit, quantification limit, range and stability of the sample solution were evaluated. Under the experimental conditions, the conditions of the method were demonstrated by TLC-Scanner and optimization was carried out for an injection volume of 3 µL, radioactive concentration of 10 mCi/mL and carrier volume of 40 µL. It was statistically demonstrated that the method is selective for the 131I iodide band Rf of 0,8 and for the radiochemical impurity IO₃⁻ Rf of 0.6, linearity from 6,0 to 22.0 mCi/mL, intermediate precision with Global RSD of 0,624%, robustness with global RSD 0,101%, detection limit of 0,09 mCi/mL, quantification limit of 0.53 Ci/mL, conforming range, and stability of the sample solution evaluated over time 0, 2 and 20 hours with a global RSD of 0,362%, obtaining consistent results. The development of the method based on AQbD allowed the generation of a design space and an operational space with knowledge of all the characteristics and limitations of the method, likewise in all the operations the conformity of the tests to the acceptance criteria was verified. The validity of our method is concluded under the established conditions, suitable for use in the manufacturing process of sodium iodide 131I and application in nuclear medicine services.

Deep learning is emerging in many industrial sectors in hand with big data analytics to streamline production. In the biomanufacturing sector, big data infrastructure is lagging comparatively to other industries. A promising approach is to combine Deep Neural Networks (DNN) with prior knowledge in Hybrid Neural Network (HNN) workflows that are less dependent on the quality and quantity of data. This paper reviews published articles over the past 30 years on the topic of HNN applications to bioprocesses. It revealed that HNNs were applied to various bioprocesses, including microbial cultures, animal cells cultures, mixed microbial cultures, and enzyme biocatalysis. HNNs were mainly applied for process analysis, process monitoring, development of software sensors, open- and closed-loop control, batch-to-batch control, model predictive control, intensified design of experiments, quality-by-design, and recently for the development of digital twins. Most previous HNN studies combined shallow Feedforward Neural Networks (FFNNs) with physical laws, such as macroscopic material balance equations, following the semiparametric design principle. Only recently, deep HNNs based on deep FFNNs, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM) networks and Physics Informed Neural Networks (PINNs) have been reported. The biopharma sector is currently a major driver but applications to biologics quality attributes, new modalities, and downstream processing are significant research gaps.

Most head and neck cancers are diagnosed in advanced stages, when the curative interventions are no longer possible. The assessment and the multidisciplinary therapeutic approach of the locally advanced cases are difficult since the onset of the disease becomes a significant challenge for the whole attending team (including both the patient and his family) because they have to deal with to an extensive symptomatology (abundant secretions, refractory pain, mutilations predominantly in the cephalic area), with the cure of stomas (tracheostomy, gastrostomy) and with various post-therapeutic sequelae. The present paper reflects the impact of late diagnosis, the complexity of the multimodal specific oncological treatment (chemotherapy, radiotherapy, immunotherapy, pal-liative and terminal treatment), the adaptation of medical care to the psycho-emotional structure, having as an example the case of 54-year old patient (with his consent) diagnosed with pharyn-golaryngeal neoplasm who presented himself to “St. Luca” Chronic Disease Hospital, the Oncol-ogy-Palliative Care Department, in September 2021. In patients with locally advanced head and neck cancers, besides the specifically oncological therapeutic decisions, the empathic-emotional connection between the medical team with the patient and his family plays a key role in the ther-apeutic conduct.

Esterases are hydrolases that catalyze the hydrolysis of esters into the corresponding acids and alcohols. The development of fluorescent probes for detecting esterases is of great importance due to their wide spectrum of biological and industrial applications. These probes can provide a rapid and sensitive method for detecting the presence and activity of esterases in various samples, including biological fluids, food products, and environmental samples. Fluorescent probes can also be used for monitoring the effects of drugs and environmental toxins on esterase activity, as well as to study the functions and mechanisms of these enzymes in several biological systems. Additionally, fluorescent probes can be designed to selectively target specific types of esterases, such as those found in pathogenic bacteria or cancer cells. In this review, we summarize the recent fluorescent probes described for the visualization of cell viability and some applications for in vivo imaging. On the other hand, Positron Emission Tomography (PET) is a nuclear-based molecular imaging modality of great value to study the activity of enzymes in vivo. We provide some examples of PET probes for imaging acetylcholinesterases and butyrylcholinesterases in brain, which are valuable tools for diagnosing dementia and monitoring the effects of anticholinergic drugs on the central nervous system.

Nowadays, mindfulness-based interventions (MBI) have experimented a remarkable development of studies among childhood and adolescent interventions. For this reason, dispositional mindfulness (DM) measures for children and adolescents have been developed to determine the effectiveness of MBI at this age stage. However, little is known about how key elements of DM (f. e., cognitive de/fusion or experiential avoidance that both conform psychological inflexibility) are involved in the mechanisms of the children and adolescents’ mental health outcomes. This research examined the mediating effect of cognitive fusion between DM and anxiety and other negative emotional states in a sample of 318 Spanish primary-school students (aged between 8 and 16 years, M=11.24, SD=2.19, 50.8% males). Participants completed the AFQ-Y, which is a measure of psychological inflexibility that encompasses cognitive defusion and experiential avoidance; CAMM (DM for children and adolescents), PANAS-N (positive and negative affect measure for children, the Spanish version of PANASC), and STAIC (an anxiety measure for children). The study accomplished ethical standards. As MBI relevant literature has suggested, cognitive defusion was a significant mediator between DM and symptoms of both negative emotions and anxiety in children and adolescents. However, experiential avoidance did not show any significant mediating relationship. Probably, it is needed improvement of the assessment of experiential avoidance. MBI programs for children and adolescents may include more activities for reducing the effects of the cognitive defusion on their emotional distress.

Advances in next-generation sequencing have facilitated the discovery of a multitude of long non-coding RNAs (lncRNAs) with pleiotropic functions in cellular processes, disease and viral pathogenesis. It came as no surprise when viruses were also revealed to transcribe their own lncRNAs. Among them, gammaherpesviruses, one of the three subfamilies of the Herpesviridae, code their largest number. These structurally and functionally intricate non-coding (nc) transcripts modulate cellular and viral gene expression to maintain viral latency or prompt lytic reactivation. The lncRNAs allow the virus to escape cytosolic surveillance, sequester and re-localize essential cellular factors and modulate the cell cycle and proliferation. Some viral lncRNAs act as “messenger molecules”, transferring information about viral infection to neighboring cells. This broad range of lncRNA functions is achieved through lncRNA structure-mediated interactions with effector molecules of viral and host origin, including other RNAs, proteins and DNAs. In this review, we discuss examples of gammaherpesvirus-encoded lncRNAs, emphasize their unique structural attributes, and link them to viral life cycle, pathogenesis and disease progression. We will address their potential as novel targets for drug discovery and propose future directions to explore lncRNA structure and function relationship.

One of the needs of the teaching and learning processes is the lack of information during the process, such as the emotions of students. Emotions influence learning, the ability to process information and accurately understand what we are dealing with. They profoundly affect students’ academic engagement and performance. One new way of getting such information is monitoring students' emotions. This research aims to expose 6 groups of secondary school students to video recordings for further analysis and categorization of their emotions. A model of emotional recognition (ER) during classroom learning was designed, with a custom-made code, from recorded videos to images to identify faces, action units (AUs) and consequently the emotions of each of the students shown on the screen. In addition, the ER model was optimized, from detecting few students to many students during a class. Emotions were then analysed according to the academic year, subject, and comparing the emotions at the beginning and at the end of the class. The results indicate the presence of a variety of emotions in the classroom and we found significant differences in the presence of some emotions depending on the time of class, subject and academic year, although there are no clear patterns. We discussed how emotions influence students' academic performance, and we suggest future research focus on teachers utilizing tools like this to improve student well-being and performance.

Autoimmune blistering diseases represent a group of chronic severe, disabling, potentially fatal disorders of the skin and/or mucous membranes primarily mediated by pathogenic auto-antibodies. Despite their rarity, these diseases are associated with significant morbidity and mortality, a profound negative impact on the patient’s quality of life and impose a considerable economic burden. Rituximab, an anti CD-20 monoclonal antibody represents the first line of therapy for pemphigus, regardless of its severity as it ensures high rates of rapid, long-lasting complete remission. Nevertheless, disease recurrence is the rule, all patients requiring maintenance therapy with rituximab sooner or later. While innate resistance to rituximab in pemphigus patients is exceptional, acquired resistance is frequent and may develop even in patients with initial complete response to rituximab, representing a real challenge for physicians. We discuss the various resistance mechanisms and their complex interplay, as well as the numerous therapeutic alternatives that may be used to circumvent rituximab resistance. As no therapeutic measure is universally efficient, individualization of rituximab treatment regimen and tailored adjuvant therapies in refractory pemphigus cases are mandatory.

The kinase pathway plays a crucial role in blood vessel function. Particular attention is paid to VEGFR-type 2 angiogenesis and vascular morphogenesis as the tyrosin kinase pathway is preferentially activated. In silico studies were performed on several peptides that affect VEGFR2 in both stimulating and inhibitory ways. This investigation aims to examine the molecular properties of VEGFR2, a molecule primarily involved in the processes of vasculogenesis and angiogenesis. These relationships were defined by the interactions between vascular endothelial growth factor receptor 2 (VEGFR2) and the structural features of the systems. The chemical space of the inhibitory peptides and stimulators was described using topological and energetic properties. Furthermore, chimeric models of stimulating and inhibitory proteins (for VEGFR2) were computed using the protein system structures. The interaction between the chimeric proteins and VEGFR was computed. The chemical space was further characterized using complex manifolds and high-dimensional data visualization. The results show that a slightly similar chemical area is shared by VEGFR2 and is shared by stimulating and inhibitory proteins. On the other hand, the stimulator peptides and the inhibitors have distinct chemical spaces.

Coffee is one of the most valuable agricultural products worldwide, and it is crucial to have efficient tools to obtain reliable information about production. This study aims to estimate coffee plantation production using segmentation and deep learning techniques in RGB images. Photographs of coffee plants were taken in Tabaconas, San Ignacio-Cajamarca, to create a dataset of crops during the harvest stage. The images were segmented to detect coffee fruits. A deep learning method was developed with YOLOv5 to detect the fruits and OpenCV to count them. The results showed that YOLOv5 achieved an accuracy of 97.25%, a recall of 95.77%, and an F1-Score of 96.37%, demonstrating high reliability in detecting coffee fruits. The average detection time per image was 17.9 seconds. The metrics were evaluated using a confusion matrix, highlighting the model's good performance. In conclusion, segmentation and deep learning techniques, along with counting algorithms developed with OpenCV, proved effective for estimating coffee production. This approach provides a valuable tool for farmers, improving crop management and facilitating decision-making in precision agriculture.

Ultrasonic imaging & NDE applications can greatly improve their signal-to-noise ratios (SNR) by driving each transducer (composing piezoelectric arrays) with a spike giving pulsed power of k-Watts, repetitively at a PRF = 5000 spikes/s, by using a HV capacitive-discharge generator. However very-high levels, of pulsed intensities (3-10 A) and voltages (300-700 V) must be considered for a rigorous spike modeling. Even though the consumed "average" power will be small, the intensity through each transducer achieves several amperes, so the pulsed powers delivered by each HV generator can attain levels higher than in CW high-power ultrasonic applications: e.g., up to 5 kW / spike. This is concluded here from a transient modeling of the loaded generator. Then, unforeseen phenomena rise: intense brief pulses of driving power & emitted force in transducers, and non-linearities in driver semiconductors, because their characteristic curves only include linear ranges. But fortunately, piezoelectric devices working in this intense regime do not show serious heating problems, because the average power remains being moderate. Intensity, power and voltage, driving a broadband transducer from a HV capacitive pulser, are calculated to drastically improve (in ≅ 40 dB) the ultrasonic net dynamic range available, with emitted forces ≅ 250 Newtons pp and E/R received pulses of 70 V pp.

Knowledge of the agricultural soil microbiota, of the microbial consortia that comprise it, and the promotion of agricultural practices that maintain and encourage them, is a promising way to improve soil quality for sustainable agriculture and to provide food security. Although numerous studies have demonstrated the positive effects of beneficial soil microorganisms on crop yields and quality, the use of microbial consortia in agriculture remains low. Microbial consortia have more properties than an individual microbial inoculum, due to the synergy of the microorganisms that make them up. This review describes the main characteristics, ecosystem functions, crop benefits and biotechnological applications of microbial consortia composed of arbuscular mycorrhizal fungi, plant growth promoting bacteria and actinobacteria, to promote the restoration of agricultural soils and, consequently, the quality and health of agricultural crops. The aim is to provide knowledge that will contribute to the development of sustainable and sufficiently productive agriculture, which will adapt in a good way to the pace of the growing human population and to climate change.

The microorganisms able of accumulating lipids in high percentages, known as oleaginous microorganisms, have been widely studied as an alternative for producing oleochemicals and biofuels. Microbial lipid, so called Single Cell Oil (SCO), production depends on several growth parameters, including the nature of the carbon substrate, which must be efficiently taken up and converted into storage lipid. Οn the other hand, substrates considered for large scale applications must be abundant and of low acquisition cost. Among others, lignocellulosic biomass is a promising renewable substrate containing high percentages of assimilable sugars (hexoses and pentoses). However, it is also highly recalcitrant and therefore it requires specific pretreatments in order to release its assimilable components. The main drawback of lignocellulose pretreatment is the generation of several by-products that can inhibit the microbial metabolism. In this review, we discuss the main aspects related to the cultivation of oleaginous microorganisms using lignocellulosic biomass as substrate, hoping to contribute to the development of a sustainable process for SCO production in the near future.

This work studies the discontinuities features of sedimentary flysch materials in a 100 km2 area belonging to the Basque Arc. Such materials are common in this Spanish Alpine region located in the north of the Iberian Peninsula. A total of 33 outcrops are investigated by an intensive geotechnical investigation including geomechanical stations, boreholes and mechanical laboratory tests. Two flysch units are characterized: the Upper Aguinaga Formation or siliciclastic flysch, and the Lower Itziar Formation or calcareous flysch. Differences between both flysch formation are found. Joints in the siliciclastic flysch formation present an undulated roughness, with a spacing narrower and a persistence lower than in the calcareous flysch formation, which exhibits higher friction angles, although roughness is essentially planar. In addition, the potential of using Artificial Intelligence (AI) techniques, particularly Artificial Neural Networks and Support Vector Machine, to estimate the Geological Strength Index (GSI) from the Rock Quality Design (RQD) and some discontinuities features (spacing, persistence, aperture and roughness) is investigated. AI techniques are found to be satisfactory, being the Support Vector Machine with a linear kernel the technique which achieves the best performance.

In recent years, the emergence of the concept of immunometabolism has shed light on the pivotal role that cellular metabolism plays in both the activation of immune cells and the development of immune programs. The antiviral response, a widely distributed defense mechanism used by infected cells, serves to not only control infections but also to attenuates their deleterious effects. The exploration of the role of metabolism in orchestrating the antiviral response represents a burgeoning area of research, especially considering the escalating incidence of viral outbreaks coupled with the increasing prevalence of metabolic diseases. Here, we present a review of current knowledge regarding immunometabolism and the antiviral response during viral infections. Initially, we delve into the concept of immunometabolism by examining its application in the field of cancer—a domain that has long spearheaded inquiries into this fascinating intersection of disciplines. Subsequently, we explore examples of immune cells whose activation is intricately regulated by metabolic processes. Progressing with a systematic and cellular approach, our aim is to unravel the potential role of metabolism in antiviral defense, placing significant emphasis on the innate and canonical interferon response.

This article aims to delve into the Equity, Diversity and Inclusivity (EDI) issues prevalent in the engineering disciplines in Canada and Spain, shedding light on the common obstacles faced by underrepresented individuals and highlighting potential strategies to foster a more inclusive and diverse engineering community in these nations. Two strategic lines have been identified: (a) facilitating university education access to underrepresented and minority groups, and (b) Accompanying and guiding such students during university training, setting them up for successful future careers. The article also shows the sets of strategies employed in Canada and Spain, clearly distinguishing the approach taken in the two countries. While in Canada, there is a more decentralized approach wherein the universities device their strategies and agenda to address EDI issues, in Spain there is a stronger and direct involvement of the government to ensure a comprehensive, system-wide approach to tackling EDI issues in academia.

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.

Recognizing the critical impact of environmental factors on individuals, this study explores the relationship between environmental indoor pollutants (PM1, PM2.5, PM10, and CO₂) and students' basic emotional responses based on Ekman’s categorization. Conducted in a secondary school in Spain, it integrates IoT and image processing technologies to monitor air quality and emotions in real-time. Participants included 76 secondary school students and three teachers, with data collected over two months. The results showed significant correlations between PM levels and negative emotions such as anger and disgust, while CO₂ levels were associated with both negative and positive emotions, including happiness. Regression models demonstrated that environmental variables significantly predict basic emotions, highlighting the influence of indoor air quality. These findings emphasize the need for proactive air quality management in educational settings to enhance learning environments and support students' emotional well-being.