The digital transformation of critical infrastructures, such as energy or water distribution systems, is essential for their smart management. Faster issue identification and smoother services enable better adaptation to consumers' evolving demands. However, these large-scale infrastructures are often outdated. Their digital transformation is crucial to enable them supporting societies. This process must be carefully planned, providing guidance that ensures that the data they rely on is dependable and that the system remains fully operational during the transition. This paper presents a formal model that supports reliable data acquisition in legacy critical infrastructures, facilitating their evolution towards a data-driven smart system. Our model provides the foundation for a flexible transformation process while generating dependable data for system management. We demonstrate the model's applicability in a use case within the water distribution domain and discuss its benefits.

Mesoscale eddies wield a significant influence on primary productivity in marine ecosystems by regulating nutrient availability, vertical mixing, and phytoplankton growth dynamics. In this study, we tracked and analyzed the effects of mesoscale eddies on net primary productivity (NPP) across the Bay of Bengal (BoB) using remote sensing data. Dividing the Bay into six zones based on mesoscale eddy frequency and distribution, our analysis identified 1880 anticyclonic eddies and 1972 cyclonic eddies during January 2010–March 2020 monitoring period. Cyclonic eddies predominantly occurred in the western part of the bay - along the east coast of the Indian Peninsula; while anticyclonic eddies were also observed, albeit in lesser proportions. Among eddies lasting one-week, anticyclonic eddies comprised approximately 48.81%, while cyclonic eddies constituted approximately 51.19% of the total. Analysis of the NPP distribution across the months revealed intriguing patterns. Mean values of NPP fluctuated throughout the year, with the highest value observed in August (748.51 mg C/m2/day) and the lowest in May (519.26 mg C/m2/day). The findings indicate a complex relationship between eddy distribution and NPP, with Zones 1 and 2 exhibiting a higher occurrence of cyclonic eddies, correlating with greater NPP and its variability. Conversely, Zones 3 and 5 display increased eddy activity despite fewer cyclonic eddies and lower NPP levels. Zone 6 shows reduced eddy activity and NPP, while Zone 4 presents moderate eddy activity alongside lower NPP. In contrast, Zones 3 to 5 exhibit lower NPP levels despite exhibiting heightened eddy activity. This study contributes valuable insights into the dynamics of ocean circulation and the impacts of eddies on NPP, which can inform fisheries management strategies, advances climate resilience measures, expands scientific knowledge, and guides policies related to conservation and sustainable resource utilization.

For a linear ordinary differential equation (ODE in short) of the third order, results are presented that supplement the theory of conjugate points and extremal solutions by W. Leighton, Z. Nehari, M. Hanan. It is especially noted the sensitivity of solutions to the initial data, which makes their numerical study difficult. Similar results were obtained for the third-order nonlinear equations of the Emden-Fowler type.

Significant changes in Land Use and Land Cover (LULC) have widespread implications for the environment, economy, and society; influencing future sustainability and development of a region. This study aimed to assess LULC changes for a 30 year period (1990 – 2020) and project future LULC from 2030 to 2100 for the Irrawaddy Delta using remote sensing and simulations with the artificial neural networks-cellular automata method. The findings showed significant LULC changes in the Delta, particularly for the mangrove forests and cropland (rice paddies). Mangrove coverage was 1,471 km² in 1990 but decreased to 1,282 km² in 2020, and simulations predict a further reduction to 1,277 km² in 2100. Cropland areas increased from 10,550 km² to 10,618 km² in 2020, with simulations projecting a slight decrease to 10,586 km² by 2100. Human activities and cyclonic events, especially in the southern part of the region, have led to barren land and impervious areas replacing dense mangrove and forested areas. These changes threaten the ecological integrity of the Delta and impact local livelihoods and biodiversity. The study underscores the need for sustainable land management practices and policies to mitigate the adverse effects of LULC changes and ensure the resilience of the Irrawaddy Delta against ongoing environmental challenges.

The elastic wave equation with the seismic tensorial force is solved in a homogeneous and isotropic medium (the Earth). Spherical-shell waves are obtained, which are associated to the primary P and S seismic waves. It is shown that these waves produce secondary waves with sources on the plane surface of a half-space, which have the form of abrupt walls with a long tail, propagating in the interior and on the surface of the half-space. These secondary waves are associated to the seismic mainshock. The results, previously reported, are re-derived by using Fourier transformations and specific regularization procedures. The relevance of this seismic motion for the ground motion, the seismographs' recordings and the effect of the inhomogeneities in the medium are discussed.

For a long time, there has been interest in the relationship between personality traits and life satisfaction. However, many previous studies suffer from small sample sizes or selective sampling, sometimes leading to biased or imprecise results. The current study, which focuses on the trait of extraversion, attempts to overcome these limitations by using a large-scale German survey of more than 40,000 individuals aged 10 to 72. As the descriptive and regression results clearly show, there is a statistically significant relationship between extraversion and several dimensions of current life satisfaction. Depending on the type of satisfaction, the unstandardized regression coefficients range from 0.18 to 0.33. To gain further insight, age is added as an explanatory variable to test whether these associations change as a person ages. The results show that the effect sizes sometimes differ by age but remain robust and statistically significant. In conclusion, the study adds to the literature by providing convincing evidence that extraversion and life satisfaction are positively associated, at least in Western and industrialized countries, and that there are interaction effects with age.

The higher education sector in Africa has experienced remarkable growth over the past decades, enrolling and graduating millions of students annually. Despite this progress, high unemployment rates among graduates and pervasive underdevelopment have raised questions about the relevance of higher education in Africa. Critics have intensely scrutinized the quality of curricula, highlighting a significant mismatch between the skills offered and the demands of the job market. This disconnect is often due to curricula that are unresponsive to both job requirements and students' needs. Enhanced pedagogical approaches are essential to address this issue. Community engagement and service learning (CE&SL) offer promising solutions by bridging the gap between theoretical knowledge and practical application. Recognizing the potential benefits, higher education institutions across the continent are gradually integrating CE and SL into their teaching and research frameworks. However, the adoption of these approaches has been slow. This paper explores the opportunities and challenges hindering the effective and widespread implementation of CE and SL in African higher education institutions and proposes practical strategies to overcome these obstacles. By embracing these innovative approaches, African universities can better prepare graduates for the dynamic job market and contribute more effectively to the continent's development.

Nitrogen (N) is an essential nutrient and plays an important role in plant growth and physiology. In addition, N is also the limiting nutrient in most terrestrial ecosystems. The increasing use of N fertilizers increases agricultural production, but also has negative impacts on biodiversity, water quality and increases emissions of greenhouse gases such as nitrogen oxides (NOx) and nitrous oxide (N2O) into the atmosphere. N2O is a strong greenhouse gas and the product of microbial transformation processes of N introduced into soil and groundwater (nitrification and denitrification). The production of N2O in soils is highly dependent on oxygen and water content, soil temperature and texture and the available amount of reactive nitrogen (NO3- or NH4+). In agricultural soils, N2O emissions are also influenced by the type of fertilizer used, crops grown, soil pH and NO3- concentration. Refined forms of land management, such as the cultivation of legumes, can reduce the use of fertilizers and thus also the emission of N2O. Legumes can use symbiotic nodule bacteria (rhizobia) to bind atmospheric N2 and make it available to the plant. Non-symbiotic soil microorganisms such as cyanobacteria or other heterotrophic and autotrophic prokaryotes are also able to fix N2. Furthermore, the N2-fixing enzyme nitrogenase, which is specific for most organisms, is not specific for other N2 compounds, especially N2O. To study the N2 and N2O fixation potential of soils and legumes, experiments with isotope-enriched N-gases (100 mol% 15N2 and 15N2O) were performed. Three different soil types (forest, meadow and wetland) as well as legume plants inoculated with rhizobia bacteria (Rhizobium leucaneae) (Leucaena leucocephala) were incubated in microcosms with different mixing ratios of N2 and N2O over a period of one week. The measured 15N enrichment was then used to determine the biological uptake rates. Both in plants and in soils admixtures of up to 40% N2O had no influence on the N2 fixation rate. N2 uptake rates were 1.2 ± 0.4 ug N gdw-1 d- 1in forest and grassland soils and 3.9 ± 1.2 ug N gdw-1 d- 1 in wetland soils. In contrast, the N2 fixation rates of leguminous plants were significantly higher (130 ± 40 ug N gdw-1 d- 1), with the highest accumulation not in root nodules but in the roots. In both plants and soil, the N2O fixation of 0.2 ± 0.1 ug N gdw-1 d- 1 could only be measured from a concentration of 4 vol%. The results indicate that both soils and legumes have a high potential to bind atmospheric nitrogen in the form of both N2 but not N2O. The fate of nitrogen in soil needs to be further investigated. N2 fixation seems to play an important role in wetland soils. Legumes in particular have the potential for NH4+ input and N2O reduction, as most of the solid nitrogen has been transferred to the roots, which can contribute significantly to soil nutrient input.

Multiple imputation with chained equations (MICE) is a widespread approach to account for missing data in empirical research. Combining MICE with bootstrapping, that is, repeatedly resampling with replacement from the data to estimate variances and confidence intervals of statistics of interest, is not straightforward. The current document provides an overview of how to use bootstrapping with imputed data in Stata. Two main approaches (impute first and then bootstrap or vice-versa) are discussed and shortly compared. Code is provided for Stata.

The evolutionary origin of the genome remains elusive. Here, I hypothesize that its first iteration, the protogenome, was a multi-ribozyme RNA. It evolved, likely within liposomes (the protocells) forming in dry-wet cycling environments, through the random fusion of ribozymes by a ligase and was amplified by a polymerase. The protogenome thereby linked, in one molecule, the information required to seed the protometabolism (a combination of RNA-based autocatalytic sets) in newly forming protocells. If this combination of autocatalytic sets was evolutionarily advantageous, the protogenome would have amplified in a population of multiplying protocells. It likely was a quasispecies with redundant information, e.g., multiple copies of one ribozyme. As such, new functionalities could evolve, including a genetic code. Once one or more components of the protometabolism were templated by the protogenome (e.g., when a ribozyme was replaced by a protein enzyme), and/or addiction modules evolved, the protometabolism became dependent on the protogenome. Along with increasing fidelity of the RNA polymerase, the protogenome could grow, e.g., by incorporating additional ribozyme domains. Finally, the protogenome could have evolved into a DNA genome with increased stability and storage capacity. I will provide suggestions for experiments to test some aspects of this hypothesis.

Several studies suggest that children infected with SARS-CoV-2 have fewer clinical manifestations than adults; when they develop symptoms, they rarely progress to severe disease. Different immunological theories have been proposed to explain this phenomenon. In September 2020, 16% of the active COVID-19 cases in Venezuela were children under 19 years. We conducted a cross-sectional study of pediatric patients' immune response and clinical conditions with SARS-CoV-2 infection. The patients were admitted to the COVID-19 area of the emergency department of Dr José Manuel de los Ríos Children's Hospital (2021-2022). The lymphocyte subpopulations were analysed by flow cytometry, and IFNγ, IL-6 and IL-10 serum concentrations were quantified using commercial ELISA assays. The analysis was conducted on 72 patients aged one month and 18 years. The majority, 52.8%, had mild disease, and 30.6 % were diagnosed with MIS-C. The main symptoms reported were fever, cough and diarrhoea. A correlation was found between IL-10 and IL-6 concentrations and age group; lymphocyte subpopulations and nutritional status and steroid use; IL-6 concentrations and clinical severity. The results suggest a different immune response depending on age and nutritional status that should be considered for treating pediatric COVID-19 patients.

The German Constitutional Court’s climate verdict provides a re-interpretation of liberal- democratic core concepts and is highly relevant for liberal constitutional law in general – including EU and international law. The verdict accepts human rights as intertemporal and globally applicable; it applies the precautionary principle to these rights and frees them from the misleading causality debate. However, the court fails to address the most important violations of human rights, and it categorised climate policy as a greater threat to freedom than climate change. And the court does not make it clear that the Paris 1.5-degree limit implies a radically smaller carbon budget. Furthermore, little attention has so far been paid to the fact that the ruling implies an obligation for more EU climate protection, especially since most emissions are regulated supranationally. To be effective, the EU emissions trading system demands a reform, which should go well beyond the existing EU proposals to enable societal transformation to sustainability.

Bootstrapping is a flexible, powerful and well-established statistical approach to quantify the uncertainty of virtually any point estimate. While multiple versions of bootstrap confidence intervals are already available in Stata, dbs implements the double (iterated) bootstrap. Instead of relying on parametric assumptions such as the non-parametric resampling bootstrap confidence interval does, it is more flexible and derives critical values directly from that data. To do so, multiple methods are available (analytic approach, double resampling, jackknife estimation). In a comparative simulation study it is empirically demonstrated that the strengths of the double bootstrap are particularly evident for small samples (n < 100) when heteroscedasticity is present. While all other approaches result in undercoverage, only the double bootstrap reaches the target coverage level and hence avoids incorrect statistical conclusions. The computational burden is not even necessarily larger than for other bootstrap approaches.

The food system, the most important driver of planetary transformation, is in a deep crisis. Therefore, seeking a sustainable and socially-fair transition pathway becomes an issue of utmost priority for our own survival. The consideration of food as a commodity, a social construct that played a central role in driving this crisis, remains the uncontested narrative to lead the different transition pathways what seems rather contradictory. By exploring the normative values in the transition landscape, this paper seeks to understand how relevant is the hegemonic narrative of “food as commodity” and its alternative of “food as commons” to determine transition trajectories and food policy beliefs. Applying the Multi-level Perspective framework and developing the ill-studied “agency in transition”, this research enquired food-related professionals that belong to an online community of practice (N=95) on valuation of food dimensions and agency in food transitions to check whether the valuation of food is relevant to explain personal stances in transition. Results suggest the socially-constructed view of food as commodity is positively correlated to the gradual reforming attitude, whereas food as commons is positively correlated to the counter-hegemonic transformers regardless the self-defined position in the transition landscape (regime or niches). At personal level, there are multiple loci of resistance with counter-hegemonic attitudes in varied institutions of the regime and the innovative niches, many of them holding this discourse of food as commons. Conversely, alter-hegemonic attitudes are not positively correlated to this alternative discourse and they may inadvertently or purportedly reinforce the ‘‘neoliberal narrative’’. Food as commons, a different narrative whose rationale is explained in the paper, seems to be a relevant framework that could enrich the multiple transformative constituencies that challenge the industrial food system and therefore facilitate the convergence of movements that reject the commodification of food.

With the developments of smart technologies, the use of rare earth elements (REEs) knows a widespread use, thus, their importance as valuable and strategic metals boosted to levels never known before. Due to their scarcity in Earth crust, the recovery of these elements from secondary resources also knows further developments. Traditional pyrometallurgical and hydrometallurgical processing, though of wide use, in the recovery of these REEs, have some environmental drawbacks, thus, the development of new recovery approaches are under developments. Here, Solvometallurgy appeared as a friendly environmental technology, and ionic liquids and deep eutectic solvents re-sulted as a first-row chemicals to be used in the different unit operations used in solvometallurgical processing: leaching, liquid-liquid extraction, ion exchange (adsorption), precipitation and elec-trolysis. This manuscript reviewed the most recent literature concerning the use of ionic liquids and deep eutectic solvents in the recovery of REEs from various sources.

Pathological calcifications may consist of calcium oxalate (CaOx), hydroxyapatite phosphate (HAP), and brushite (BRU). The objective of this study was to evaluate the effect of phytate (inositol hexakisphosphate, InsP6), InsP6 hydrolysates, and individual lower InsPs (InsP5, InsP4, InsP3, and InsP2) on the crystallization of CaOx, HAP and BRU in artificial urine. All of the lower InsPs seem to inhibit the crystallization of calcium salts in biological fluids, although our in vitro results showed that InsP6 and InsP5 were stronger inhibitors of CaOx crystallization, and InsP5 and InsP4 were stronger inhibitors of BRU crystallization. For the specific in vitro experimental conditions we examined, the InsPs had very weak effects on HAP crystallization, although it is likely that a different mechanism is responsible for HAP crystallization in vivo. For example, calciprotein particles seem to have an important role in the formation of cardiovascular calcifications in vivo. The experimental conditions that we examined partially recapitulated the in vivo conditions of CaOx and BRU crystallization, but not the in vivo conditions of apatite crystallization.

Multiple imputation by chained equations (MICE) is a popular and well-researched statistical approach to account for missing data in empirical research. However, applying the technique requires researchers to set dozens of smaller and larger parameters to build an adequate imputation model before estimating the analytical model of interest. It is somewhat unclear how severely small and potentially arbitrary decisions influence the quality of the produced findings. The current study tests this empirically using a simulation approach with datasets with low and high shares of missing data points that are missing at random (MAR). For each of the two specifications, 4,200 simulations are conducted where multiple parameters are randomly varied to create a diverse range of potential imputation models. The results demonstrate that even random imputation models can significantly reduce bias compared to listwise deletion since more than 90% of all simulations give less biased results. All minor decisions taken together explain between 11% and 21% of the variation in the statistics of interest. The most substantial influence on this variation is due to the selection of the imputation algorithm within MICE. These findings demonstrate that almost any imputation model, even those built with little care, will often result in a higher quality than applying listwise deletion, as long as critical assumptions, such as MAR and the avoidance of severe misspecifications, hold.

Regression models are highly popular in empirical research and come in many different forms to fit virtually any distribution, variable, or research question. Usually, these models also compute how much variation in the outcome variable can be explained by all predictors, which is relevant to understanding whether the predictors are, in sum, able to explain the outcome or whether other potentially unobserved factors are more relevant. This aspect is crucial for interventions and policy as even statistically significant regression coefficients can be meaningless if they have little influence on the outcome overall. Besides having a measurement to judge the overall goodness of fit, ranking predictors by their relative importance is also relevant. For such analyses, it is necessary to decompose the total explanatory power of a model and partition it so that each explanatory variable is assigned a share. This enables the computation of a predictor variable's absolute and relative influence. Dominance analysis is a statistical approach to achieve this goal.

Following Smolin, we proceed to unification of general relativity and quantum theory by operating solely with events, i.e., without appealing to physical systems and space-time. The universe is modelled as a dendrogram (finite tree) expressing the hierarchic relations between events. This is the observational (epistemic) model; the ontic model is based on p-adic numbers (infinite trees). Hence, we use novel mathematics—not only space-time but even real numbers are not in use. Here, the p-adic space (which is zero dimensional) serves as the base for the holographic image of the universe. In this way our theory relates to p-adic physics; in particular, p-adic string theory and complex disordered systems (p-adic representation of Parisi matrix for spin glasses). Our Dendrogramic-Holographic (DH) theory matches perfectly with the Mach’s principle and Brans-Dicke theory. We found surprising informational interrelation between the fundamental constants, h, c, G, and their DH-analogues, h(D), c(D), G(D). DH-theory is part of Wheeler’s project on the information restructuring of physics. It is also a step towards the Unified Field theory. The universal potential V is nonlocal, but this is relational DH-nonlocality. V can be coupled to the Bohm quantum potential by moving to the real representation. This coupling enhanced the role of the Bohm potential.

Rapid peri-urbanization has resulted in increasing demand for and pressure on peri-urban lands at the expense of agricultural lands. Households’ decision to convert from agricultural land uses to residential and commercial land uses is driven by a myriad of factors, ranging from social to economic, in the Asante-Akim South district of the Asante region, Ghana. The paper examined the effects of agricultural land use trade-off on food production in the district. Using a triangulation of qualitative and quantitative methods, 115 household respondents were proportionately sampled from three selected communities in the district, for the collection of data through the administration of questionnaires. The data were subjected to the Pearson’s chi-square, embedded in the SPSS V.16, to test for association among the variables. We report that the increasing rate of agricultural land uses conversions was as a result of increasing demand for residential and commercial land usage at the expense of agricultural land uses. Converting prime agricultural lands into other land uses was seen as profitable to agricultural expansion. A re-examination of the district land use plans by the Ghanaian Physical (Town and Country) Planning Department in tandem with the Lands Commission is therefore recommended.

Recently we started the development of Holographic Dendrogramic Theory (DH-theory). It is based on the novel mathematical representation of the relational event universe (in the spirit of (Smolin, Barbour, Rovelli). Elementary events are represented by branches of dendrograms, finite trees, which are generated from data with clustering algorithms. In this note we study the dynamics of the event-universe generated by the appearance of a new event. Generally, each new event can generate the complete reconstruction of the whole dendrogramic universe. However, we found (via numerical simulation) unexpected stability of this universe. Its events are coupled via the hierarchic relational structure which is relatively stable with respect even random generation of new events. We also observe the regularity patterns in location of new events on dendrograms. In the curse of evolution, the dendrogram’s complexity increases and determine the arrow of time the event universe. We use the complexity measure from particle shape dynamics which was shown to be increase in both direction away from a Janus point and thus determine the arrow of time in symmetrical manner away from a Janus point. The particle shape dynamics theory is a relational theory with close ideological resemblance to DH-theory as both relays on Mach’s principle and Leibniz’s relationalism and his principles. By using the complexity measure on dendrograms and its p-adic string representation, we demonstrate the emergence of time arrow from the p-adic zero-dimensional field, where space and time are absent.

Viral infections as well as changes in the composition of the intestinal microbiota and virome have been linked to cancer. Moreover, the success of cancer immunotherapy with checkpoint inhibitors has been correlated with the intestinal microbial composition of patients. The transfer of feces – which contains mainly bacteria and their viruses (phages) – from immunotherapy responders to non-responders, known as fecal microbiota transplantation (FMT), has been shown to be able convert some non-responders to responders. Since phages may also increase the response to immunotherapy, for example by inducing T cells cross-reacting with cancer antigens, modulating phage populations may provide a new avenue to improve immunotherapy responsiveness. In this review, we summarize the current knowledge on the human virome and its links to cancer, and discuss the potential utility of bacteriophages in increasing the responder rate for cancer immunotherapy.

One hundred and twenty (120) fingerlings of Clarias gariepinus (mean weight: 0.96 ± 0.1g) were randomly exposed to 4 experimental treatments of petroleum, based on LC₅₀ values (6.4mg/L of crude oil, 8.7mg/L of petrol, 8.0mg/L of kerosene and 7.8mg/L of diesel oil) and replicated thrice, to determine polycyclic aromatic hydrocarbons (PAH) in exposed fish for 96 h. There was no significant difference (P > 0.05) in total (PAHs) between crude oil (97.1 ng/uL) and diesel (97.2 ng/uL) exposed fish and also between petrol (53.2 ng/uL) and kerosene (49.6 ng/uL) exposed fish, but there was a significant difference (P < 0.05) in PAH levels of the crude oil/diesel exposed -groups of fish compared to petrol/kerosene exposed -groups of fish (97.1/97.2 and 53.2/49.6 ng/uL). Naphthalene correlated positively to benzo a anthracene (r=0.672, (P < 0.05), benzo b fluoranthene (r=0.681, P < 0.05) and chrysene (r=0.615, P < 0.05) but did not correlate to fluorene. Benzo a anthracene correlated positively to benzo a pyrene (r=0.578, P < 0.05), phenathrene (r=0.685, P < 0.05) but did not correlate to acenaphthene. Fluorene correlated positively to benzo a pyrene (r=0.695, P < 0.05) but did not correlate to chrysene. Chrysene correlated positively to dibenzo a,h, pyrene (r=0.658, P < 0.05) to phenathrene and benzo b fluoranthene (r=0.659, P< 0.05). Indeno 123 cd- pyrene and fluranthene however did not correlate to other PAHs except naphthanene, acenaphthene and acenaphthylene. The level of PAH in fish may translate to the toxicity effect since crude oil and diesel with lower LC₅₀ (6.4 and 7.8 mg/L) deposited greater PAH than kerosene and petrol with higher LC₅₀ (8.7 and 8.0 mg/L) in fingerlings of C. gariepinus. High risk to cancer disorders may occur in exposed fish to petroleum with high incidence of fluorene , anthracene, pyrene and benz a anthracene which correlated positively to benzo a pyrene which provide some basis for predicting impact of oil spills on fingerling population.

The legume-rhizobia symbiosis is one of the most important plant-microbe interactions in sustainable agriculture due to its ability to provide much needed N to cropping systems. This interaction is mediated by the mutual recognition of signaling molecules from the two partners, namely legumes and rhizobia. With legumes, these molecules are in the form of flavonoids and anthocyanins, which are responsible for the pigmentation of plants parts, such as seeds, flowers, fruits and even leaves. Seed coat pigmentation in legumes is a dominant factor influencing gene expression relating to N2 fixation, and may be responsible for the different N2-fixing abilities observed among legume genotypes under field conditions in African soils. Cowpea, Kersting’s bean and Bambara groundnut landraces with black seed coat color are reported to release higher concentrations of nod-gene-inducing flavonoids and anthocyanins when compared to the Red and Cream landraces, hence the black seed coat pigmentation is considered a biomarker for enhanced nodulation and N2 fixation. Cowpea, Bambara groundnut and Kersting’s bean with differing seed coat colors are known to attract different native soil rhizobia, confirmable by PCR-RFLP analysis of bacterial DNA from root nodules of these legumes. Even when seeds of the same legume with diverse seed coat colors were planted together in one hole, the nodulating bradyrhizobia clustered differently in the PCR-RFLP dendrograms. In one study, Kersting’s groundnut, Bambara groundnut and cowpea with differing seed coat colors were selectively nodulated by different bradyrhizobial species. Multilocus sequence analysis showed that different Bradyrhizobium species nodulated the Kersting's bean based on seed coat color. Phylogenetic analysis also placed the bradyrhizobial isolates in close proximity to different Bradyrhizobium species such as B. vignae 7-2T, B. subterraneum 58 2-1T, B. kavangense 14-3T, B. liaoningense 2281 (USDA 3622)T, B. yuanmingense LMG 21827T, B. huanghuaihaiense CCBAU 23303T, B. pachyrhizi PAC48T, and a reference type strain of B. elkanii according to seed coat color. Using 16S rDNA amplicon sequencing, we also found significant selective influences of seed coat pigmentation on microbial community structure in the rhizosphere of five Kersting’s groundnut landraces. For example, the rhizosphere of Belane Mottled landrace was dominated by Proteobacteria, while Bacteroidetes dominated the rhizospheres of the other landraces. With legumes, seed coat pigmentation therefore plays a dominant role in the selection of the bacterial symbiotic partner.

The design of curved surface sliders (CSS) based on the elastic response spectrum is done by iteration to find the combination of friction coefficient and displacement capacity which satisfies the condition that the maximum horizontal CSS force is equal to the horizontal force of the structure. Although this CSS design is valid it does not necessarily minimize structural acceleration. This paper therefore describes the optimum CSS design for minimum structural acceleration. All valid CSS designs and the optimum CSS design are represented by their associated trajectory in the elastic response spectrum plane which visualizes the optimization problem. The results demonstrate that the optimum CSS design is not obtained at maximum tolerated effective damping ratio. The subsequent sensitivity analysis describes how much the structural acceleration increases if the actual friction coefficient of the real CSS deviates from its optimum design value. The analysis points out that the increase in structural acceleration is approximately one order of magnitude smaller than the deviation in friction. The sensitivity data may be used by structural engineer to determine tolerable deviations in friction coefficient which still results in acceptable structural accelerations.

In this paper we use the Mellin convolution theorem, which is related to Perron's formula. Also we introduce new explicit formulae for arithmetic function which generalize the explicit formulae of Weil for other arithmetic functions different from the Von-Mangoldt function.

The purpose of this study is to compare IVC Celect and ALN filters in regard to their efficacy, retrievability, and 1-year follow-up after retrieval. Materials and Methods: This is a prospective randomized study, conducted in three centers between April 2020 and May 2021. A total of 115 participants were randomized, of which 15 participants were excluded for various reasons. Each group of 50 participants was finally assigned a type of filter (Celect n= 50 and ALN= 50). Tilt angles at placement and retrieval together with rates of overall filter retrieval, complications, complex retrieval, and clinical follow-up at 12 months were compared. Results: One hundred participants (59 men and 41 women) were included. The mean age was 62.4±13.3 with no significant differences between both groups (p 0.503). The mean of dwelling time was 44.7±93 days. (p 0.520) Filter retrieval was successful in all participants (100%). The main complication in CT prior to removal was inclination > 15º (31%) and filter tip embedment (16%). No significant differences were observed in the type of retrieval (standard or complex) between both filters (p 0.24); however, fluoroscopy time was significantly longer in the complex removal of the Celect filter 29.1±12 min vs 17.5±10.3 (p 0.005). After one year, no recurrent pulmonary embolism was observed in both types of filters. Conclusion: The ALN filter had a significantly lower rate of tip and filter tip embedding with no differences in complexity or removal success rate. There were significant differences in the fluoroscopy time consumed for standard and complex retrievals between both filters with less time in the ALN filter

Over the last decade, the prevalence of health issues has increased by approximately 29.1%, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly, however many present approaches are unsuitable for real-world implementation due to high memory footprints and lack of interpretability. We introduce DeClEx, a pipeline designed to address these issues. DeClEx ensures that data mirrors real-world settings by incorporating gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state of the art pre-trained models while achieving threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification and explainability in a single pipeline called DeClEx.

The accurate prediction of heat load profiles with a daily resolution is required for a broad range of applications such as potential studies, design, or predictive operation of heating systems. If the heat demand of a consumer is mainly caused by (production) processes independent of the ambient temperature, existing load profile prediction methods fail. To close this gap, this study develops two ex post machine learning models for the prediction of the heat demand with a daily resolution. The selected input features are commonly available to each consumer connected to public natural gas and electricity grids or operating an energy monitoring system: Ambient temperature, weekday, electricity consumption, and heat consumption of the last seven days directly before the predicted day. The study’s database covers electricity and natural gas consumption load profiles from 82 German consumers over a period of two years. Electricity and heat consumption correlate strongly with individual patterns for many consumers. Both, shallow and deep learning algorithms are evaluated. The highest accuracy is achieved by a Long Short Term Memory (LSTM) model with a median of R² of 0.94. The ex post model architecture makes the model suitable for automated anomaly detection in energy monitoring systems.

The boosted interest in the use of rare earth elements (REEs) in modern technologies had also increase the necessity of their recovery from various sources, including raw materials and wastes. Though Hydrometallurgy plays a key role in these recovery processes, some drawbacks (apparent or not) of these processes, had led to the development of a more environmental friendship subclass named Solvometallurgy, in which non-aqueous solvents substituted to the aqueous media of the hydrometallurgical processing. The non-aqueous solvents chosen for these usages are, besides ionic liquids (ILs), the so-named Deep Eutectic Solvents (DEEs). The utilization of DEEs included the leaching of REEs from the different sources containing them, and also in the separation-purification steps necessary for the yielding of these elements, normally as oxides or salts, in the most purified form. This work reviewed the most recent literature (2023 year) about the utilization of deep eutectic solvents in the recovery of REEs from various sources, and in the coupling of these two (DESs and REEs) to derived compounds to be used in other fields.

Parallel decompositions have proved to be powerful tools for the analysis and interpretation of the physical information provided by Mueller matrices experimentally obtained. In this work, the procedure for the so-called arbitrary decomposition of Mueller matrices is validated through its application to a set of representative experimentally determined Mueller matrices. The covariance and passivity criteria required for the physical realizability of the Mueller matrices involved in the parallel decompositions are integrated in the procedure, which ensures the physical consistency of the results presented.

This paper is devoted to the foundational problems of dendrogramic holographic theory (DH-theory). We use the ontic-epistemic (implicate-explicate order) methodology. The epistemic counterpart is based on representation of data by dendrograms constructed with hierarchic clustering algorithms. The ontic Universe is described as the p-adic tree; it is zero dimensional, totally disconnected, disordered, and bounded (in p-adic ultrametric). Interrelation classical-quantum loses its sharpness; generally simple dendrograms are ``more quantum’’ than complex one. We use the CHSH-inequality as a measure of quantum(-likeness). We demonstrate that it can be violated by classical experimental data represented by dendrograms. The seed of this violation is neither nonlocality nor rejection of realism. This is nonergodicity of dendrogramic time series. Generally, violation of ergodicity is one of the basic features of DH-theory. We also consider DH-theory for Minkovski geometry and monitor the dependence of CHSH-violation and nonergodicity on geometry as well as a Lorentz transformation of data.

proposal for a fundamental theory is described in which classical and quantum physics as a representation of the universe as a gigantic dendrogram are unified. The latter is the explicate order structure corresponding to the purely number-theoretical implicate order structure given by p-adic numbers. This number field was zero-dimensional, totally disconnected, and disordered. Physical systems (such as electrons, photons) are sub-dendrograms of the universal dendrogram. Measurement process is described as interactions among dendrograms; in particular, quantum measurement problems can be resolved using this process. The theory is realistic, but realism is expressed via the the Leibnitz principle of the Identity of Indiscernible. The classical-quantum interplay is based on the degree of indistinguishability between dendrograms (in which the ergodicity assumption is removed). Depending on this degree, some physical quantities behave more or less in a quantum manner (versus classic manner). Ideologically, our theory is very close to Smolin’s dynamics of difference and Rovelli’s relational quantum mechanics. The presence of classical behavior in nature implies a finiteness of the Universe-dendrogram. (Infinite Universe is considered to be purely quantum.) Reconstruction of events in a four-dimensional space type is based on the holographic principle. Our model reproduces Bell-type correlations in the dendrogramic framework. By adjusting dendrogram complexity, violation of the Bell inequality can be made larger or smaller.

We provide a biochronology of Jurassic planktonic foramininfera, using first order linkage to ammonite and nannofossil stratigraphy and geochronology. This enigmatic and understudied group of microfossils occurred from middle Toarcian through Tithonian time, from ~180 to ~143 Ma; its origin is unknown. There are three genera: Globuligerina, Conoglobigerina and Petaloglobigerina. The genus Globuligerina, with a smooth to pustulose test surface texture appeared in Toarcian (late Early Jurassic) and Conoglobigerina, with a rough reticulate test surface texture in Oxfordian (early Late Jurassic) time. The genus Petaloglobigerina, with a petaloid last whorl and one or more twisted and claviform chambers evolved in early Kimmeridgian time from Globuligerina balakhmatovae. We recognize stratigraphic events from eleven species across four evolutionary lineages, calibrated to Geologic Time Scale 2020. A dramatic faunal change over, which is not well documented led to the survival of only one taxon, most likely Gobuligerina oxfordiana in the Tithonian. During the Berriasian several new taxa appeared.

This study investigated the breakdown trend in an automated production with an aim to recommend the application of Reliability-centered maintenance (RCM) for an improved productivity via a new preventive maintenance (PM) program. Individual Section-forming machine (ISM): a glass blowing machine for making glass bottles was used as the case study of an automated production system. The machine parts and the working mechanisms were analysed with a special focus on methods of processes and procedures that will enable the ISM maintenance department run more effective and achieve its essential goal of ensuring effective machine operation and reducing machine downtime. In this work, information is provided on the steps and procedures to identify critical components of the ISM using Failure Modes and Effect Analysis (FMEA) as a tool to develop an optimal maintenance program based on the reliability data of the equipment’s functional components. A relationship was established between the failure rate of the machine components and the maintenance costs such that using the recommended PM program, an evidence of improvement in the machine’s availability, safety and cost-effectiveness will result into an increase in the company’s profit margin.

A reduced order model is developed to monitor aeroengines condition (defining their degradation from a baseline state) in real-time, by using data collected in specific sensors. This reduced model is constructed by applying higher order singular value decomposition plus interpolation to appropriate data, organized in tensor form. Such data are obtained using a detailed engine model that takes the engine physics into account. Thus, the method synergically combines the advantages of data-driven (fast online operation) and model-based (the engine physics is accounted for) condition monitoring methods. Using this reduced order model as surrogate of the engine model, two gradient-like condition monitoring tools are constructed. The first tool is extremely fast and able to precisely compute `on the fly’ the turbine inlet temperature, which is a paramount parameter for the engine performance, operation, and maintenance, and can only be roughly estimated by the engine instrumentation in civil aviation. The second tool is not so fast (but still reasonably inexpensive) and precisely computes both, the engine degradation and the turbine inlet temperature at which sensors data have been acquired. These tools are robust in connection with random noise added to the sensors data and can be straight forwardly applied to other mechanical systems.

In the whole world, including Mexico, the rising prevalence of diabetes poses significant challenges to healthcare systems, with a notable impact on hospital admissions even being an ambulatory care sensitive condition, that means, hospital admissions are avoidable. Traditional healthcare methodologies have been instrumental in managing diabetes and preventing complications, yet they often face limitations such as merging, cleansing, and outlier analysis of health data to identify and address diseases effectively. This paper aims to address this gap by conducting a comprehensive comparison of the methodologies used in healthcare and data science for this purpose. This work uses hospital diabetes discharge records from 2010 to 2023, a total of 36,665,793 records, which belong to medical units of the Ministry of Health of Mexico. In this work, we seek to provide the arguments why as a data scientist it is mandatory to learn the field of knowledge of the problem and its implications if this is not done, and therefore to disclose insights that can help in policy decisions and reduce the burden of avoidable hospitalizations. The approach is mainly based on the standardization or adjust rates by sex and age groups. This study provides the foundations for a new way of data scientist must deal with health data.

Though nowadays germanium do not reach the range of popularity than other metals, i.e. rare earth elements, its utility in target industries makes of it also a strategic metal. Though germanium can be find in a series of raw materials, the principal source for its recovery is from secondary wastes of the zinc industry, and also, the recycle of germanium-bearing waste materials is becoming of interest. In this recovery, Hydrometallurgy is performing a key role to the successful achievement of this goal. The present work reviews the most recent applications (2023 and 2024 years) of hydrometallurgical operations on the recovery of germanium from different solid and liquid sources.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

Lead-210 from natural atmospheric fallout is widely used in multidisciplinary studies to date recent sediments. Some of the ²¹⁰Pb-based dating models can produce historical records of sediment accumulation rates (SAR) and initial activity concentrations ( ). The former have been profusely used to track past changes in the sedimentary conditions. Both physical magnitudes are differently affected by model errors (those arising for the partial or null accomplishment of some model assumptions). This work is aimed at assessing the effects on SAR and of model errors in the CRS, CS, PLUM and TERESA dating models, due to random variability in ²¹⁰Pb fluxes, which is a usual sedimentary condition. Synthetic cores are used as virtual laboratories for this goal. Independently of the model choice, SARs are largely affected by model errors, resulting in some large and spurious deviations from the true values. This questions their general use for tracking past environmental changes. are less sensitive to model errors and their trends of change with time may reflect real changes in sedimentary conditions, as it is shown with some real cores from varved sediments.

In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called ‘life’ ―due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions― it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.

We fabricate large-area atomically thin MoS₂ layers through the direct transformation of crystalline molybdenum trioxide (MoO₃) by sulfurization at relatively low temperatures. The obtained MoS₂ sheets are polycrystalline (~10-20 nm single-crystal domain size) with areas of up to 300×300 µm² with 2-4 layers in thickness and show a marked p-type behaviour. The synthesized films are characterized by a combination of complementary techniques: Raman spectroscopy, X-ray diffraction, transmission electron microscopy and electronic transport measurements.

The Neotropical region is one of the most diverse regions of the globe in terms of macro-organismic species. Regarding the microbial world, however, little is known about the diversity and biogeography patterns of micro-organisms in the Neotropics. In this context, the study of several microbial taxonomic groups is still missing and/or incomplete, such as the protists. Our goal here was to summarize the available information of Neotropical protists, focusing on molecular data from environmental continental samples, to explore what these data evidence on their ecology and biogeography. For this, we reviewed the findings from all articles that focused on or included the terrestrial protists using metabarcoding approach and identified the gaps and future perspectives in this research field. We found that Neotropical protists diversity patterns seem to be, at least in part, congruent with that of macro-organisms and, different than plants and bacteria, just weakly explained by environmental variables. We argue that studies with standardized protocols including different biomes are necessary to fully characterize the ecology and biogeography on Neotropical protists. Furthermore, dismember evolutionary lineages and functional guilds of protists are important to better understand the relationship between diversity, dispersal abilities and functionality of particular taxa of protists in their habitats.

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.

A Twi-English parallel corpus is certainly an important resource for Machine Translation of Twi (ISO 639-3), a Low-Resource African Language (LRAL) which is mainly spoken in Ghana and Ivory Coast. Currently large-scale multi-domain Twi-English parallel corpus is still unavailable partly due to the difficulties and the arduous efforts required in its design. In this paper, we present TWIENG: a large-scale multi-domain Twi-English parallel corpus. We crawled the sentences from the web using web crawlers, translated, aligned, tokenized and compiled to create the corpus. We crawled English sentences from Ghanaian indigenous electronic news portals, Ghanaian Parliamentary Hansards, Twi Bible and crowdsourcing via google forms. The sentences were translated by professional translators and linguists, they were then aligned, tokenized and compiled. The corpus was curated using the sketch engine, a corpus manager and analysis software developed by Lexical Computing Limited. The corpus was manually evaluated by Twi professional linguists. The Corpus has 5,419 parallel sentences.

We study the efficient computation of power indices for weighted voting games with precoalitions amongst subsets of players (reflecting, e.g., ideological proximity) using the paradigm of dynamic programming. Starting from the state-of-the-art algorithms for computing the Banzhaf and Shapley-Shubik indices for weighted voting games we present a framework for fast algorithms for the three most common power indices with precoalitions, i.e. the Owen index, the Banzhaf-Owen index and the Symmetric Coalitional Banzhaf index, and point out why our new algorithms are applicable for large numbers of players. We discuss implementations of our algorithms for the three power indices with precoalitions in C++ and review computing times as well as storage requirements.

This document summarizes the evidence currently available about the effects of the anesthetic agents and techniques used in primary cancer surgery and long-term oncologic outcomes, and the biomolecular mechanisms involved in their interaction..

Background: The Victorian era in Great Britain was a historical period that brought about profound changes for humanity. The confluence of various factors fostered the development of numerous scientific disciplines. In the field of health sciences, Florence Nightingale played a central role. Following her training as a nurse and her role as superintendent during the Crimean War, she made decisive contributions to establishing a public health network. Methods: This is a retrospective historical heuristic and hermeneutic study analyzing documentation of Nightingale's contributions to public health from around 1890 to 1900. The historical method was used to collect, classify, and analyze primary and secondary sources relevant to the study's objectives. Results: Nightingale supported the development of the concept of “health at home” by training women to implement healthy measures that contributed to the well-being of families and communities. Through the training and development of a formal “Health Missioners program”, she provided the necessary guidance to improve the health of rural communities across the English countryside. Conclusion: The role of Health Missioners has persisted, as health visitors continue to visit homes in the United Kingdom. Therefore, the contribution of Florence Nightingale to public health is unquestionable. This study was not registered.

Rice is currently the most important food crop in the world and we are only just beginning to study the bacterial associated microbiome. It is of importance to perform screenings of the core rice microbiota and also to develop new plant-microbe models and simplified communities for increasing our understanding about the formation and function of its microbiome. In order to begin to address this aspect, we have performed the isolation of hundreds bacterial isolates obtained from endorhizosphere of two rice cultivars from Venezuela. The validation of plant-growth promoting bacterial activities in vitro has led us to select and characterize 15 isolates for in planta studies such as germination test, endophytism ability and plant growth promotion. Consequently, a set of 10 isolates was selected for the set-up of an endophytic consortium as a simplified model of the natural rice bacterial endomicrobiota. Upon inoculation, the colonization and abundance of each strain within the rice roots was tracked by a culture-independent technique in gnotobiotic conditions in a 30 days period. Four strains belonging to Pseudomonas, Agrobacterium and Delftia genera have shown a promising capacity for colonizing and coexistence in root tissues. On the other hand, a bacterial community taxonomic profiling of the rhizosphere and the endorhizosphere of both cultivars were obtained and are discussed. This study is part of a growing body of research on core crops microbiome and simplified microbiomes, which strengthens the formation process of the endophytic community leading to a better understanding of the rice microbiome.

With the megatrend of digitalization, the demand for sensors in previously difficult to access scenarios is increasing. Filament-shaped sensors (FSS) are ideal for this demand especially in applications in which the monitoring of textile structures is the focus. Electrically conductive bicomponent filaments based on thermoplastic polyurethane (TPU) and doped with carbon nanotubes (CNTs) offer great potential due to the flexible mechanical properties. Through the core-conducting, bicomponent structure the sensing material is protected from environmental factors such as surrounding conductive materials and external moisture. The insulating material, however, simultaneously complicates the contacting method in order to measure sensing changes in the conductive core. In this work laser cutting is employed as a technology in order to expose the conductive core of the filaments. The filament is then coated with silver and mechanically crimped, providing both a conductive interface for the data acquisition device as well as a protective layer. Laser parameters (power and speed) are investigated in order to identify the parameters with the best cutting properties which is analyzed visually as well as electrically. The work conducted here can then be used in order to provide a robust and reproducible contacting method for core-conducting TPU filaments for strain sensing applications.

Diabetes mellitus (DM) is one of the most dangerous metabolic diseases with high rate of mortality worldwide. It is well known that insulin resistance and deficiency in insulin production from pancreatic β-cells are the main characteristic of DM. Due to the detrimental side effects of the current treatment, there is a considerable need to develop new effective antidiabetic drugs, especially alpha-glucosidase and alpha-amylase inhibitors with lesser adverse effects. These inhibitors are known to be directly involved in the delay of carbohydrate digestion, resulting in a reduction of glucose absorption rate and consequently reduce the post-prandial raise of plasma glucose, which can reduce the risk of long-term diabetes complications. Hence, natural products are well-known sources for the discovery of new scaffold for drugs discovery, including new antidiabetic drugs. The phytochemical investigation of Salvia aurita collected from Hogobach pass, Eastern Cape, South Africa (SA), yielded four known abietane diterpenes namely carnosol (1), rosmanol (2), 7-methoxyrosmanol (3), 12-methoxycarnosic acid (4) and one flavonoid named 4,7-dimethylapigenin (5). Structural characterization of these isolated compounds was conducted using 1 and 2D NMR, in comparison with reported spectroscopic data. These compounds are reported for the first time from S. aurita. The biological evaluation of the isolated compound against alpha-glucosidase exhibited strong inhibitory activities for 3 and 2 with IC50 values of 4.2 ± 0.7 and 16.4 ± 1.1 µg/mL respectively, while 4 and 1 demonstrated strong alpha-amylase inhibitory activity amongst the isolated compounds with IC50 of 16.2 ± 0.3 and 19.8 ± 1.4 µg/mL. Molecular docking analysis confirms strong inhibitory activity of 3 against alpha-glucosidase. Additionally, excellent antioxidant capacities were displayed by 2, 1 and 3 respectively as ORAC (25789.9 ± 10.5; 23961.8 ± 14.1; 23939.3 ± 2.4) µM TE/g; 1 and 2 as FRAP (3917.8 ± 2.1; 1522.3 ± 0.9) µM AAE/g; 5 and 2 as TEAC (3190.4 ± 2.8; 2055.0 ± 2.6) µM TE/g. The methanolic extract of S. aurita is a rich source of abietane diterpenes with excellent antioxidant and anti-diabetic activities that can be useful to modulate oxidative stress, and might possibly be excellent candidates for the management of diabetes. This is the first scientific report on the phytochemical isolation and biological evaluation of alpha-glucosidase and alpha-amylase inhibitory activities of Salvia aurita.

In this work, a small-strain phase-field model is presented, which is able to predict crack propagation in systems with anisotropic brittle and ductile constituents. To model the anisotropic brittle crack propagation, an anisotropic critical energy release rate is used. The brittle constituents behave linear-elastically, in a transversely isotropic manner. Ductile crack growth is realised by a special crack degradation function, depending on the accumulated plastic strain, which is calculated by following the J2-plasticity theory. The mechanical jump conditions are applied in solid-solid phase transition regions. The influence of the relevant model parameters on a crack, propagating through a planar brittle-ductile interface, and furthermore a crack developing in a domain with a single anisotropic brittle ellipsoid, embedded in a ductile matrix, is investigated. We demonstrate that important properties, concerning the mechanical behaviour of grey cast iron, such as the favoured growth of cracks along the graphite lamellae and the tension-compression load asymmetry of the stress-strain response, are covered by the model. The behaviour is analysed on basis of a simulation domain consisting of three differently oriented elliptical inclusions, embedded in a ductile matrix, which is subjected to tensile and compressive load. The used material parameters correspond to graphite lamellae and pearlite.

Rice is currently the most important food crop in the world and we are only just beginning to study the bacterial associated microbiome. It is of importance to perform screenings of the core rice microbiota and also to develop new plant-microbe models and simplified communities for increasing our understanding about the formation and function of its microbiome. In order to begin to address this aspect, we have performed the isolation of bacterial strains from the endorhizosphere of two rice cultivars from Venezuela. The validation of plant-growth promoting bacterial activities in vitro has led us to select and characterize 15 isolates for in planta studies such as germination test, endophytism ability and plant growth promotion. Consequently, a set of 10 isolates was selected for the set-up of an endophytic consortium as a simplified model of the natural rice bacterial endomicrobiota. Upon inoculation, the colonization and abundance of each strain within the rice roots was tracked by a culture-independent technique in gnotobiotic conditions in a 30 days period. Four strains belonging to Pseudomonas, Agrobacterium and Delftia genera have shown a promising capacity for colonizing and coexistence in root tissues. On the other hand, a bacterial community taxonomic profiling of the rhizosphere and the endorhizosphere of both cultivars were obtained and are discussed. This study is part of a growing body of research on core crops microbiome and simplified microbiomes, which strengthens the formation process of the endophytic community leading to a better understanding of the rice microbiome.

Background: The hydatidiform moles remain prevalent in spectrum of gesta-tional trophoblastic diseases (GTDs). In resource-limited settings like Rwanda, the definitive diagnosis relies upon single of histomophological diagnosis. The histomorphology alone suffers from high interobserver and intra-observer vari-ability with poor diagnostic reproducibility. The present study aimed at deter-mining the role of p57 immunophenotyping in the validation of histomorpholog-ical diagnosis of hydatidiform moles. Methods: A retrospective cross-sectional study embarked for histological cases collected between January 2017 and June 2020. A review of Hematoxylin &Eosin(H&E) stained slides was performed with subsequent p57 immunohisto-chemical staining. Results: Recorded were 211 retrospective cases of hydatidiform moles and 96 (45.9%) cases were all subjected to p57 immunohistochemical staining consid-ered as gold standard diagnostic modality in the present study. As result, the sensitivity and specificity of the histomophological diagnosis of complete hyda-tidiform mole were estimated at 62.5% and 57.1% respectively with positive and negative likelihood ratio of 0.145 and of 0.54 respectively. PPV and NPV were 81.8% and 29.3%, respectively. Whereas of 57.1% and 79.2% with PPV and NPV of 42.9% and 83.8% respectively for partial hydatidiform moles. Per the Youden J statistics method, the accuracy estimation of histomophological diagnosis of hydatidiform mole (HM) was 0.196 (CHM) and 0.336(PHM). Conclusions: This study highlighted a need to integrate p57 immunostaining in routine histopathological diagnosis of hydatidiform moles refining the defini-tive diagnosis.

The Autopoiesis and Cognition Theory (ACT), by Maturana and Varela, based on the notions of Biological Closure and Structural Coupling, is a well-known theory on how to understand biological organization [1, 2, 3]. Although, for example, the Free Energy Principle framework evokes some entailments of autopoiesis in a more formal setting [4, 5]; and ACT has been used in many fields, its impact has been restricted because it lacks quantitative analysis. Here we present a theoretical framework grounded in accepted and well-developed ideas from Mathematics and Physics which advance the understanding of the Principles of Biological Organization under the guidance of Biological Closure and Structural Coupling. The disciplines of Differential Geometry/Topology, Mechanics and Complex Dynamical Systems provide a powerful, elegant, and well-established body of knowledge to support our Biological Organization Principles (BOP) framework. In particular, Stochastic Mechanics and KAM theory (from Kolmogorov, Arnold and Moser theorem) allow us to develop, using the notions of Biological Closure and Structural Coupling, a central core of BOP termed Dynamical Closure Mechanism. Under the proposed framework, a wide variety of bio- logical phenomena can be understood, shedding new light on biological explanations. However, an understanding of biological organization may require the re-evaluation of dogmas on how we think on biology as it seems inescapable that what is needed is an integration of analysis and notions derived from mathematics, physics, and biology to generate a new landscape of ideas.

The solvent extraction of gold(III) by undiluted 2-ethylhexanol or dissolved in toluene from HCl solution has been investigated. The numerical analysis of gold distribution data suggests the formation of HAuCl4·L and HAuCl4·2L (L= 2-ethylhexanol) species in the organic phase with formation constants K11= 38 and K12= 309, respectively. The results derived from gold(III) distribution have been implemented in a solid-supported liquid membrane system. The influence of several variables on gold transport was considered: feed and receiving phases stirring speeds, HCl and gold concentrations in the feed phase and carrier concentration in the membrane phase as well as the presence of base metals (Fe,Cu,Ni) and PGMs in the feed phase. Also, diffusional resistances to mass transfer are estimated. Gold is recovered as zero valent nanoparticles.

The importance of rare earth elements as the basis in the development of new technologies or the improvement of the used ones, made of a necessity its recovery, besides that from raw materials, from waste materials. In this recovery, Hydrometallurgy and its derivative Solvometallurgy, play a key role due to its operational characteristics, which are emphasized with the use of ionic liquids. The manuscript reviewed the most recent advances (2023 and 2024 years) about the use of ionic liquids in the unit operations (leaching and separation technologies) aimed to the recovery of these valuable and strategic metals. Moreover, a comprehensive review about the use of these chemicals in the development of advanced materials containing some of these rare earth elements is presented.

LLMs are a compressed repository of a vast corpus of valuable information on which they are trained. Therefore, this work hypothesizes that LLMs such as Llama, Orca, Falcon, and Mistral can be used for misinformation detection by making them cross-check new information with the repository on which they are trained. Accordingly, this paper describes the findings from the investigation of the abilities of LLMs in detecting misinformation on multiple datasets. The results are interpreted using explainable AI techniques such as LIME, SHAP, and Integrated Gradients. The LLMs themselves are also asked to explain their classification. These complementary approaches aid in better understanding the inner workings of misinformation detection using LLMs and lead to conclusions about their effectiveness at the task.

: Schizophrenia and schizoaffective disorder are generally treated with second-generation antipsychotic drugs. These drugs are mostly D2 and 5-HT2A antagonists. They improve positive schizophrenia symptoms sufficiently well; however, they ameliorate negative schizophrenia symptoms and cognitive functions to a small extent. We review novel antipsychotic drugs exerting a partial agonism at dopaminergic and serotonergic receptors such as cariprazine, brexipiprazole and lumateperone. Besides, the mechanisms of actions of non-anti-dopaminergic antipsychotic drugs are pointed out. Updated neural networks are used to explain the mechanism of action of M4 and M1 receptor agonists, for example xanomeline combined with trospium or emraclidine, and trace-amine-associated receptor 1 agonists (TAAR1), for example ulataront. Phase 3 clinical trials of new third generation antipsychotic drugs are presented. Novel antipsychotic drugs with a partial agonism at D2 and D3 receptors improve positive and negative schizophrenia symptoms as well as cognitive symptoms better than second generation antipsychotic drugs. Besides, they are well tolerated. M4 and M1 receptor agonists, i.e. xanomeline combined with trospium or emraclidine, and TAAR1 agonists, i.e. ulataront, have promising results in clinical trials; they well improve negative schizophrenia symptoms and cognitive functions. Phase 3 clinical trials offer promising results for anti-dopaminergic and non-anti-dopaminergic novel antipsychotic drugs. These new non-anti-dopaminergic antipsychotic drugs better emend negative schizophrenia symptoms, and they better improve cognitive functions than second-generation antipsychotic drugs. Promising new antipsychotic drugs are cariprazine, brexipiprazole, lumateperone, ulataront, and xanomeline combined with trospium. Although phase 3 clinical studies are not yet completed, they showed a therapeutic effect superior to those achieved by second-generation antipsychotic drugs. They are tolerated very well, and they better treat negative schizophrenia symptoms and improve cognitive functions.

The paper highlights the performance of the seismic isolation devices, installed on retrofitted buildings in reducing the seismic response when subjected to earthquakes. Two buildings from the beginning of the XX-th century in Bucharest are chosen from many more, monitored over the city area. We discuss the response of these base-seismic isolated structures, relying on good quality data acquired from the recent strong earthquake (03.11.2022, MW = 5.0). Elastic response spectra computed from recordings at two levels of each structure are used, placed under and right above the isolating layer. At one building the existence of previous recordings and the particularity of the sensors allow a comparison with other two relatively recent medium intensity earthquakes. The assessment is carried out in terms of maximum acceleration amax, measured at certain levels in each structure, spectral acceleration amplitude SAmax and spectral-peak corresponding period. We find that the base-isolation methodology is effective in reducing the response of the building right above the isolating layer, an observation valid for both structures, all components of the recordings, and spectral acceleration values. Moreover, the outcomes from the modal evaluation performed prior to rehabilitation and seismic isolation process are presented, by pointing out a higher newly acquired fundamental period of the isolated structures.

Background: Alcohol consumption is associated with the development of cardiovascular diseases, cancer, and liver disease. The biological mechanisms are still largely unclear. Here, we aimed to use an agnostic approach to identify phenotypes mediating the effect of alcohol on various diseases. Methods: We performed an agnostic association analysis between alcohol consumption (red, and white wine, beer/cider, fortified wine, and spirits) with over 7,800 phenotypes from the UK biobank comprising 223,728 participants. We performed Mendelian randomisation analysis to infer causality. We additionally performed a Phenome-wide association analysis and a mediation analysis between alcohol consumption as exposure, traits in causal relationship with alcohol consumption as mediators, and various diseases as outcome. Results: Of 45 traits in association with alcohol consumption, 20 were in causal relationship with alcohol consumption. Gamma glutamyltransferase (GGT; β=9.44; CI,5.94-12.93; Pfdr=9.04×10-7), mean sphered cell volume (β=0.189; CI,0.11-0.27; Pfdr=1.00×10-4), mean corpuscular volume (β=0.271; CI,0.19-0.35; Pfdr=7.09×10-10) and mean corpuscular haemoglobin (β=0.278; CI,0.19-0.36; Pfdr=1.60×10-6) showed the strongest causal relationships. We also identified GGT and physical activity as mediators causing liver cirrhosis and alcohol dependence. Conclusion: Our study provides evidence of causality between alcohol consumption and 20 traits and a mediation effect for physical activity on health consequences of alcohol consumption.

Mucosal irritation caused by cusps of upper and lower teeth represents a source of persistent, low grade mechanical trauma. This type of trauma can initiate and/or perpetuate oral lichen planus in a few susceptible patients. Here, we report a rare case of bilateral white linear striations in the buccal mucosa of a young patient, associated with sharp cusps. Oral lesions demonstrated a unique cuspal signature highlighting the causal role of subtle mucosal trauma in the genesis of reticular-oral lichen planus. Lesions appeared to be exacerbated by significant psychological distress experienced by the patient. Although the Koebner phenomenon is well reported in the cutaneous lichen planus literature, such presentations are relatively rare in the oral cavity. This report emphasizes the potential role of low-grade cuspal trauma/irritation in conjunction with psychological distress in the genesis of oral lichen planus.

Background: While greenness has been associated with lower depression, the generalizability of this association in arid landscapes remains undetermined. We assessed the association between depression and greenness among nursing students living in El Paso, Texas (the Chihuahuan desert). Methods: Depression was measured with the Patient Health Questionnaire-9 scale, and greenness with the normalized difference vegetation index (at buffer sizes =250m, 500m, 1000m). Using data from the National Land Cover Database two additional measures of land patterns were analyzed: grayness and brownness. Structural equation models were used to assess the relationships of these land patterns to depression and quantify the indirect effects of peer alienation. Results: After adjusting for individual characteristics, at buffers 250 m greenness was associated with a decrease in the Incidence Rate Ratios (IRR) of depression by 49% (IRR, 0.51; 95%CI, 0.12-2.10), greyness with increases by 64% (IRR, 1.64; 95%CI, 1.07-2.52) and brownness with decreases by 35% (IRR, 0.65; 95%CI, 0.42-0.99). At buffer 250 m peer alienation explained 17.43% (95% CI, -1.79-36.66) of the association between depression and brownness, suggesting a pathway to depression. Conclusions: We did not observe an association between depression and residential greenness in El Paso, Texas. However, we did observe a protective association between brownness and depression as well as an adverse association with grayness. These results have theoretical implications as based on commonly used frameworks in this literature and adverse association of brownness (and the lack of greenness) and depression was expected.

Introduction: Osteosarcomas of the jaw (OSJ) are rare tumors with a different behavior from osteosarcomas of other bones. This study aims to analyze the clinical, pathological, and therapeutic characteristics of this type of sarcoma. Methods: a retrospective observational study of cases diagnosed with OSJ registered at the “La Paz” University Hospital (Madrid). Results: Eight cases with a diagnosis of OSJ were obtained in a study period of 22 years (2000-2022). The mean age was 41 years. The distribution was 1:1 between the maxilla and mandible. Painful inflammation was the most frequent clinical manifestation. Conventional osteoblastic osteosarcoma was the most common. Survival at 5 years was 50%, while at 10 years, it decreased to 25%. Conclusions: OSJ differs from conventional osteosarcomas of long tubular bones. Surgery continues to be the mainstay of treatment; more studies are needed in which more standardized protocols can be proposed for adjuvant therapeutic management.

Polyurethane (PU) is a polymer widely used by humans whose recycling is highly complex due his chemical structure, being limited to incineration or accumulation in landfills. Biodegradation by enzymes and microorganisms has been studied for decades as an effective method of biological decomposition. In this study, Tenebrio molitor larvae (T. molitor) were fed with polyurethane foams, which gut enzymes and microorganisms were capable of degrading the polymer by 35% in 17 days of treatment, producing a weight loss of 14% in the mealworm. Changes in T. molitor gut bacterial community and diversity were observed, which may be due to colonization of species associated with PU degradation. Physical and structural biodegradation in PU by T. molitor compared to virgin PU, was demonstrated by Fourier Transform InfraRed spectroscopy (FTIR), Thermal Gravimetric Analysis (TGA) and Scanning Electron Microphotography (SEM).

Inflammatory bowel disease (IBD) is a chronic disease mediated by the immune system and characterized by the inflammation of the gastrointestinal tract. This study is to understand how the use of parenteral nutrition (PN) can affect the adult population diagnosed with IBD. We conducted a systematic review, meta-analysis and a meta-regression. On the different databases, (MEDLINE, Scopus, Cochrane, LILACS, CINAHL, WOS) we found 119 registers, the accuracy was 16% (19 registers); After a Full-text review, only 15 research studies were selected for qualitative synthesis and 10 for Meta-analysis and Meta-regression. The variables used were Crohn’s Disease Activity Index (CDAI), albumin, body weight (BW) and post-operative complications (COM). PN has shown to have efficacy for the treatment of IBD and is compatible with other medicines. The CDAI and albumin improve although the effect of PN are greater after a while. However, the effect on the albumin could be less than the observed value in the meta-analysis, due to a possible publication bias. The BW does not change after intervention. COM utilizing PN has been observed, although the proportion is low.

In the last two decades many detailed full transcriptomic studies on complex biological samples have been published and included in large gene expression repositories. These studies primarily provide bulk expression signal for each sample, including multiple cell-types mixed within the global signal. The cellular heterogeneity in these mixtures does not allow the activity of specific genes in specific cell types to be identified. Therefore, inferring relative cellular composition is a very powerful tool to achieve a more accurate molecular profiling of complex biological samples. In recent decades, computational techniques have been developed to solve this problem by applying cell deconvolution methods, designed to decompose cell mixtures into their cellular components and calculate the relative proportions of these elements. Some of them, only calculate the cell proportions (supervised methods), while other deconvolution algorithms can also identify the gene signatures specific for each cell type (unsupervised methods). In these work, five deconvolution methods (CIBERSORT, FARDEEP, DECONICA, LINSEED and ABIS) were implemented and used to analyze blood and immune cells, and also cancer cells, in complex mixture samples (using three bulk expression datasets). Our study provides three analytical tools (corrplots, cell-signature plots and bar-mixture plots) that allow a thorough comparative analysis of the cell mixture data. The work indicates that CIBERSORT is a robust method optimized for the identification of immune cell-types, but not as efficient in the identification of cancer cells. We also observed that LINSEED is a very powerful unsupervised method that provides precise and specific gene signatures for each of the five main immune cell-types analyzed: neutrophils and monocytes (in the myeloid lineage), B-cells, NK cells and T-cells (in the lymphoid lineage).

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

Data from NASA’s Soil Moisture Active Passive Mission (SMAP) and from the California Cooperative Oceanic Fisheries Investigations (CalCOFI) were used to examine the freshening that occurred during 2015-2016 in the Southern California Current System. Overall the freshening was found to be related to the 2014-2016 Northeast Pacific Warm Anomaly. The primary goal was to determine the feasibility of using SMAP data to observe the surface salinity signal associated with the warming. As a first step direct comparisons were done with salinity from the CalCOFI data at one-meter depth. During 2015 SMAP was saltier than CalCOFI by 0.5 PSU, but biases were reduced to < 0.1 PSU during 2016. South of 33°N, and within 100 km of the coast, SMAP was fresher in 2015 by almost 0.2 PSU. CalCOFI showed freshening of 0.1 PSU. North of 33°N SMAP and CalCOFI saw significant freshening in 2016, SMAP by 0.4 PSU and CalCOFI by 0.2 PSU. Differences between SMAP and CalCOFI are consistent with the increased stratification in 2015 and changes in the mixed layer depth.

Slow growth of calcite in confinement is abundant in Nature and man made materials. There is ample evidence that such confined growth may create forces that fracture solids. The thermodynamic limits are well known but since confined crystal growth is transport limited and difficult to control in experiment we have almost no information on the mechanisms or limits of these processes. We present a novel approach to in situ study of confined crystal growth using microfluidics for accurate control of the saturation state of the fluid and interferometric measurement of the topography of the growing confined crystal surface. We observe and explain the diffusion limited confined growth structures observed and can measure the crystal "floating" on a fluid film of 10-40~nm thickness due to the disjoining pressure. We find that there are two end member behaviours: smooth or intermittent growth in the contact region, the latter being faster than the former.

Climate change is expected to increase the occurrence of droughts with the hydrology in alpine systems being largely determined by snow dynamics. In this paper we propose a methodology to assess the impact of climate change on both meteorological and hydrological droughts taking into account the dynamics of the snow cover area (SCA). We will also analyse the correlation between these types of droughts. We have generated ensembles of local climate scenarios based on regional climate models (RCMs) representative of potential future conditions. We have considered several sources of uncertainty: different historical climate databases, simulations obtained with several RCMs, and some statistical downscaling techniques. We then used a stochastic weather generator (SWG) to generate multiple climatic series preserving the characteristics of the ensemble scenario. These were simulated within a cellular automata (CA) model to generate multiple SCA future series. They were used to calculate multiple series of meteorological drought indices, the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)) and a novel hydrological drought index (Standardized Snow Cover Index (SSCI)). A linear correlation analysis was applied to both types of drought to analyse how they propagate and the time delay between them. We applied the proposed methodology to the Sierra Nevada (southern Spain) where we estimated a general increase in meteorological and hydrological drought magnitude and duration for the horizon 2071-2100 under the RCP 8.5 emission scenario. The SCA droughts also revealed a significant increase in drought intensity. The meteorological drought propagation to SCA droughts is reflected in an immediate or short time (1 month), obtaining significant correlations in lower accumulation periods of drought indices (3 and 6 months). This will allow us to obtain information about meteorological drought from SCA deficits and vice versa.

One of the non-linear phenomena that affect high bandwidth and long reach communication systems is the non-linear phenomenon called four-wave mixing (FWM). Unfortunately, the simulation of such systems aiming to obtain their design parameter limitations require more time as the number of channels increases. In this paper, we propose a new high-performance computational model to obtain optimal design parameters in a multi san Dense Wavelength Division Multiplexing (DWDM) system, limited by FWM and the intrinsic Amplified Spontaneous Emission (ASE) noise of optical amplifiers employed in each segment. The simulation in this work provides a complete optical design characterization and compares the efficiency and speed improvement of the proposed parallelization model versus a previous sequential model. Additionally, an analysis of the computational complexity of parallel model is presented, where two parallel implementations are used. First, Open Multi−Processing (OpenMP), based on the use of a central, multi-core processing unit is used and secondly the Compute Unified Device Arquitecture (CUDA), which is based on the use of graphics processing unit. Results show that parallelism improves to up to 40 times the performance of the simulation when nested parallelization with CUDA is used, over de sequential method and up to 6 times compared with the implementation with OpenMP using 12 processors. Within our parallel implementation, it is possible to simulate with an increased number of channels, that was unpractical in the sequential simulation.

Study of micro-RNA regulatory networks (known as miRNA’s or miR’s), during development and in known pathologies have been the basis of study over the past decades. Herein, we recapitulate these findings in order to highlight the best underlying mechanisms found to date. We also seek to elucidate how miRNA dysregulation can be associated with many cardiovascular diseases. Furthermore, we discuss miR regulation mechanism during in early development in vivo and invitro. Since many of the miR’s are precursors to transcriptional regulation, we relate back to their molecular control as we can then look together at the fundamental disease they might be exacerbating by this dysregulation.

Various formulations of the exact renormalization group can be compared in the perturbative domain, in which we have reliable expressions for regularization-independent (universal) quantities. We consider the renormalization of the $\lambda\phi^4$ theory in three dimensions and make a comparison between the sharp-cutoff regularization method and other more recent methods. The former gives considerably better results, while the other methods are far from optimal in the perturbative domain. In addition, these methods present theoretical problems that are already manifest in the renormalization of mass.

This manuscript provides a new integrated view of the development of allergen-specific TH2 and the lack of their associated Treg cells in a unified model, justifying the need for IL-2 to correct allergy conditions.

Arthropod predators preying on vertebrates is generally overlooked in ecological studies, as it is not typically observed in nature and generally considered a rare event. This is likely due to the cryptic nature of these predatory events, the relatively small size of arthropods, and the difficulty in collating published data which is scattered throughout the literature. Although arthropods are known to readily hunt and consume vertebrates, very little is known about these predatory events. In this study, a systematic literature review was conducted to provide a conceptual framework, identify global patterns, and create a searchable database of arthropod preying on vertebrates. This study represents the largest global assessment of arthropod predators and vertebrate prey with over a thousand recorded observations collated from over 80 countries across every continent except Antarctica, where no arthropod predator exists. Arthropod predators were represented by six classes (insects, arachnids, centipedes, and crustaceans: Malacostraca, Ostracoda, Hexanauplia) and over 80 families. Vertebrate prey were represented by five classes (birds, mammals, reptiles, amphibians, fish) and 160 families. The most common prey were frogs consisting of over a third of all observations. The most commonly preyed reptiles were nearly all lizards, half of mammal prey were bats, nearly a third of fish were Cypriniformes, and half of bird prey were passerines. Spiders represented over half of all predatory events found and were the main predator for all vertebrates except birds, which were preyed mostly upon praying mantises. However, prey varied between spider families. For insects, true bugs (Hemiptera) and beetles preyed mostly on amphibians while the aquatic Odonata larvae preyed on amphibians and fish. Decapod predators were observed preying equally between reptiles, birds, and amphibians; with centipedes preying mainly on reptiles and mammals. Predation was mostly recorded from the Americas and Australia, with countries and regions varying between predator and prey groups. This study demonstrates that arthropods are indeed an overlooked predator of vertebrates. Recognizing and quantifying these predator-prey interactions is vital for identifying patterns and the potential impact of these relationships on shaping vertebrate populations and communities. Understanding the possible threat of arthropod predators may be especially important to improve the success of conservation efforts by accounting for predators which may currently be overlooked.

The role of invertebrate predation in shaping vertebrate communities is often underestimated or overlooked, which has resulted in the lack of their recognition in conservation planning. This is evident with predaceous diving beetles (Coleoptera: Dytiscidae) which are often the top predator in many aquatic freshwater habitats. During weekly monitoring of a compensatory habitat reintroduction for an endangered frog species, a group of a dozen adult diving beetles were encountered attacking and quickly dismembering and consuming a tadpole. A single adult diving beetle was also discovered burrowing its head deep inside and consuming a tadpole approximately three to four times its size. Although Dytiscidae are known to occasionally consume vertebrates such as tadpoles, adults are typically considered scavengers, and this communal predatory behavior and feeding method have not been previously documented. Besides these interesting novel behaviors, these observations may have implications for amphibian conservation since management efforts are not typically concerned with naturally occurring ubiquitous threats such as those from small invertebrate predators, as it is rarely been observed in nature. However, this may be perhaps due to their ability to consume prey rapidly, especially if predating in groups. Although amphibian conservation plans expect some losses from natural predation, diving beetles may affect conservation efforts such as captive breeding and reintroductions with populations already on the threshold of extinction and where every individual critical to success.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

Despite widespread use of combined antiretroviral therapy (cART) and increased life expectancy in people living with HIV (PLWH), HIV-related lymphomas (HRL) remain a leading cause of cancer morbidity and mortality for PLWH, even in patients optimally treated with cART. While incidence of aggressive forms of non-Hodgkin lymphoma decreased after cART advent, incidence of Hodgkin lymphoma (HL) has increased among PLWH in recent decades. The coinfection of Epstein Barr virus plays a crucial role in the pathogenesis of HL in the HIV setting. Currently, PLWH with HRL, including HL, are treated similarly to HIV-negative patients and, importantly, the prognosis of HL in PLWH is approaching to that of the general population. In this regard, effective chem-otherapy is strongly recommended since it has been shown to improve survival rates in all lymphoma subtypes, including HL. As a consequence, interdisciplinary collaboration between HIV specialists and hemato-oncologists for the management of potential drug-drug interactions and overlapping toxicities between antiretroviral and antineoplastic drugs is crucial for the op-timal treatment of PLWH with HL. In this article the authors review and update the epidemio-logical, clinical and biological aspects of HL presenting in PLWH with special emphasis in the improvement on prognosis and the factors that have contributed to it.

Despite widespread use of combined antiretroviral therapy (ART) and increased life expectancy in people living with HIV (PLWH), HIV-related lymphomas (HRL) remain a leading cause of cancer morbidity and mortality for PLWH, even in patients optimally treated with ART. While incidence of aggressive forms of non-Hodgkin lymphoma decreased after ART advent, incidence of Hodgkin lymphoma (HL) has increased among PLWH in recent decades. The coinfection of Epstein Barr virus plays a crucial role in the pathogenesis of HL in the HIV setting. Currently, PLWH with HRL, including HL, are treated similarly to HIV-negative patients and, importantly, the prognosis of HL in PLWH is approaching to that of the general population. In this regard, effective chemotherapy is strongly recommended since it has been shown to improve survival rates in all lymphoma subtypes, including HL. As a consequence, interdisciplinary collaboration between HIV specialists and hemato-oncologists for the management of potential drug-drug interactions and overlapping toxicities between antiretroviral and antineoplastic drugs is crucial for the optimal treatment of PLWH with HL. In this article the authors review and update the epidemiological, clinical and biological aspects of HL presenting in PLWH with special emphasis in the improvement on prognosis and the factors that have contributed to it.

Noise induces oxidative stress in the cochlea followed by sensory cell death and hearing loss. The proof of principle that injections of antioxidant vitamins and Mg²⁺ prevent noise-induced hearing loss (NIHL) has been established. However, effectiveness of oral administration remains controversial and otoprotection mechanisms unclear. Using auditory evoked potentials, quantitative PCR and immunocytochemistry, we explored effects of oral administration of vitamins A, C, E and Mg²⁺ (ACEMg) on auditory function and sensory cell survival following NIHL in rats. Oral ACEMg reduced auditory thresholds shifts after NIHL. Improved auditory function correlated with increased survival of sensory outer hair cells. In parallel, oral ACEMg modulated the expression timeline of antioxidant enzymes in the cochlea after NIHL. There was increased expression of Glutathione peroxidase-1 and Catalase at 1 and 10 days, respectively. Also, pro-apoptotic Caspase-3 and Bax levels were diminished in ACEMg-treated rats, at 10 and 30 days, respectively, following noise overstimulation, whereas, at day 10 after noise exposure, the levels of anti-apoptotic Bcl-2, were significantly increased. Therefore, oral ACEMg improves auditory function by limiting sensory hair cell death in the auditory receptor following NIHL. Regulation of the expression of antioxidant enzymes and apoptosis-related proteins in cochlear structures is involved in such otoprotective mechanism.

Freshwater fish represent half of all fish species and are the most threatened vertebrate group. Given their considerable passion and knowledge, aquarium hobbyists can play a vital role in their conservation. CARES is made up of many hobbyist organizations, whose purpose is to encourage aquarium hobbyists to the most endangered or extinct-in-the-wild freshwater fish to help ensure their survival. We found the CARES priority list contains nearly six hundred species from twenty families and two dozen species extinct-in-the-wild. The major families were typically the ones with largest hobbyist affiliations such as killifish, livebearers, and cichlids; which alone were half of CARES species. CARES contained every IUCN threatened species of Pseudomugilidae and Valenciidae, but only one percent of threatened Characidae, Cobitidae, and Gobiidae species. No Loricariidae in CARES were in the IUCN red list as they were not scientifically described. Tanzania and Mexico contained the largest amount of species, with the latter containing the most endemics. A large percent of species were classified differently than the IUCN, including a third of extinct-in-the-wild species classified as least concern by the IUCN. The vast disconnect exemplifies the importance of collaboration and information exchange required between hobbyists, the scientific community, and conservation organizations.

Vision impairment may delay responses to hazards when driving. In a proof-of-concept driving simulator study, we evaluated a hazard warning device designed for vision impaired drivers. Three groups participated: 11 persons with central vision loss (CVL; median age 60 years), 12 with homonymous field loss (HFL; 52 years) and 11 with normal vision (NV; 60 years). CVL is characterised by impaired visual acuity and contrast sensitivity while HFL is a loss of vision in the same half of the visual field (blind side) in both eyes. Participants completed drives with and without the device which gave a directional vibro-tactile warning for an approaching pedestrian hazard when collision risk exceeded a pre-defined threshold. Warnings significantly (p< 0.001) reduced brake response times for CVL (∆= 0.54s) and HFL (∆= 0.30s), but not NV participants. For HFL participants, the reduction was greater (p = 0.02) for hazards on the blind (∆= 0.57s) than seeing side (∆= 0.10s). The warnings significantly reduced collision rates for CVL participants from 11 to 0% (all hazards) and for HFL participants from 30 to 1.7% (blind side hazards). Thus, hazard warnings may be beneficial in improving safety of vision impaired drivers; further research is warranted.

For our research on droplet deformation and breakup in scaled high-pressure homogenizing units we developed a pressure stable inline droplet generator. It consists of an optically accessible flow channel with a combination of stainless steel and glass capillaries and a 3D printed orifice. The droplet size is determined online by live image analysis. The influence of the orifice diameter, the mass flow of the continuous phase and the mass flow of the disperse phase on the droplet diameter was investigated. Furthermore, the droplet detachment mechanisms were identified. Droplet diameters with small diameter fluctuation between 175 µm and 500 µm could be realized, which allows a precise adjustment of the Ca and We Number in the subsequent scaled high pressure homogenizer disruption unit. The determined influence of geometry and process parameters on the resulting droplet size and droplet detachment mechanism agreed well with literature on microfluidics. Furthermore, droplet trajectories in an exemplary scaled high-pressure homogenizer disruption unit are presented which show that the droplets can be reinjected on a trajectory close to the center axis or close to the wall, which should result in different stresses on the droplets.

We show how the excitonic features of biaxial MoS₂ flakes are very sensitive to biaxial strain. We find a lower bound for the gauge factors of the A exciton and B exciton of (-41 ± 2) meV/% and (-45 ± 2) meV/% respectively, which are larger than those found for single-layer MoS₂. Interestingly, the interlayer exciton feature also shifts upon biaxial strain but with a gauge factor that is systematically larger than that found for the A exciton, (-48 ± 4) meV/%. We attribute this larger gauge factor for the interlayer exciton to the strain tunable van der Waals interaction due to the Poisson effect (the interlayer distance changes upon biaxial strain).

Chest X-ray (CXR) is the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field-of-view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep learning-based models to estimate and correct the scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NN. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained with the MC code from chest CTs of patients affected by COVID-19. The results showed that the NN models were able to estimate and correct the scatter contribution to CXRs with an error &lt;5%, being robust to variations in the simulation setup and improving the contrast in soft tissue. The single-energy model was tested with real CXRs, providing robust estimations of the scatter-corrected CXRs.

The repeated application of herbicides has led to the development of herbicide resistance. Models are useful for identifying key processes and understanding the evolution of resistance. This study developed a spatially explicit model at a landscape scale to examine the dynamics of Lolium rigidum populations in dryland cereal crops and the evolution of herbicide resistance under var-ious management strategies. Resistance evolved rapidly under repeated herbicide use, driven by weed fecundity and herbicide efficacy. Although fitness costs associated with resistant plants re-duced resistance evolution, they did not affect the speed of spread. The most effective strategies to slow resistance involved diversifying cropping sequences (e.g., crop rotation) and the herbicide applications (e.g., rotating different herbicide modes of action). Pollen flow was the main disper-sal vector, with seed dispersal also contributing significantly. Strategies limiting seed dispersal effectively decreased resistance spread. However, the use of a seed-catching device at harvest could unintentionally enrich resistance in the area. It would be beneficial to optimise the move-ment of harvesters between fields. The model presented here is a useful tool that may assist in the exploration of novel management strategies within the context of site-specific weed management at the landscape scale, as well as in the advancement of our understanding of resistance dynamics.

Pterygium is a common ocular disease caused by abnormal cellular proliferation leading to abnormal fibrovascular growth of the conjunctiva. The main treatment is surgical removal; however, despite the improvement of surgical techniques and development of adjuvant therapies, postoperative recurrence, which can be as high as 89%, remains a challenge. Currently, pterygium excision with conjunctival autograft remains the preferred surgical technique to decrease recurrence, especially when combined with ciclosporin eye drops. Nevertheless, there is no gold standard surgical technique to prevent pterygium recurrence. Therefore, this review aims to assess the safety, effectiveness and, applicability of platelet-rich fibrin membrane for primary pterygium surgery and assess its possible benefits in resource-limited settings.

Consumption of high amounts of ethanol is a risk factor for development of cardiovascular diseases such as arterial hypertension. The hypertensive state induced by ethanol is a complex multi-factorial event, and oxidative stress is a pathophysiological hallmark of vascular dysfunction associated with ethanol consumption. Increasing levels of reactive oxygen species (ROS) in the vasculature triggers important processes underlying vascular injury, including accumulation of intracellular Ca2+ ions, reduced bioavailability of nitric oxide (NO), activation of mitogen-activated protein kinases (MAPKs), endothelial dysfunction, and loss of the anticontractile effect of perivascular adipose tissue (PVAT). The enzyme nicotinamide adenine dinucleotide phosphate (NADPH) oxidase plays a central role in vascular ROS generation in response to ethanol. Activation of the renin-angiotensin-aldosterone system (RAAS) is an upstream mechanism which contributes to NADPH oxidase stimulation, overproduction of ROS and vascular dysfunction. This review discusses the mechanisms of vascular dysfunction induced by ethanol, detailing the contribution of ROS to these processes. Data examining the association between neuroendocrine changes and vascular oxidative stress induced by ethanol are also reviewed and discussed. These issues are of paramount interest to public health as ethanol contributes to blood pressure elevation in the general population, and it is linked to cardiovascular conditions and diseases.

With metal oxide semiconductors being a promising candidate for accurate indoor air quality assessments, multiple drawbacks of the gas sensors prevent their widespread use. Examples include poor selectivity, instability over time, and sensor poisoning. Complex calibration methods and advanced operation modes can solve some of those drawbacks. However, this leads to long calibration times, which are unsuitable for mass production. In recent years, multiple attempts to solve calibration transfer have been made with the help of direct standardization, orthogonal signal correction, and many more methods. Besides those, a new promising approach is transfer learning from deep learning. This article will compare different calibration transfer methods, including direct standardization, piecewise direct standardization, transfer learning for deep learning models, and global model building. The machine learning methods to calibrate the initial models for calibration transfer are feature extraction, selection, and regression (established methods) and a custom convolutional neural network TCOCNN. It is shown that transfer learning can outperform the other calibration transfer methods regarding the root mean squared error, especially if the initial model is built with multiple sensors. It was possible to reduce the number of calibration samples by up to 99.3 % (from 10 days to approximately 2 hours) and still achieve an RMSE for acetone of around 18 ppb (15 ppb with extended individual calibration) if six different sensors were used for building the initial model. Furthermore, it was shown that the other calibration transfer methods (direct standardization and piecewise direct standardization) also work reasonably well for both machine learning approaches, primarily when multiple sensors are used for the initial model.

Shear deflection effects are traditionally neglected in most structural system identification methods. Unfortunately, this assumption might lead to significant errors in some structures, like deep beams. Although some inverse analysis methods based on the stiffness matrix method including shear deformation effects have been presented in the literature, none of these methods is able to deal with actual rotations in their formulations. Recently, the observability techniques, one of the first methods for the inverse analysis of structures included the shear effects into the system of equations. In this approach, the effects of shear rotation are neglected. When actual rotations on site are used to estimate the mechanical properties in the inverse analysis, it can result in serious errors in the observed properties. This characteristic might be especially problematic in structures such as deep beams where only rotations can be measured. To solve this problem and increase the observability techniques' applicability, this paper proposes a new approach to include shear rotations into the inverse analysis by observability techniques. This modification is based on the introduction of a new iterative process. To illustrate the applicability and potential of the proposed method, the inverse analysis of several examples of growing complexity is presented.

The formation of hydrogen sulfide (H₂S) in petroleum reservoirs by anaerobic microbial activity is called biogenic souring of reservoirs and is a risk in the oil and gas industry as the compound is extremely toxic, flammable and corrosive. In this paper, we present a workflow and the tools to assess biogenic souring from a pragmatic engineering perspective. The retention of H₂S in the reservoir due to the reactions with iron-bearing rock minerals (e.g. siderite) is shown in a theoretical approach here and supported with literature data. Cases are given for two fields under secondary (waterflooding) and tertiary flooding with microbial enhanced oil recovery (MEOR). The use of the Monte Carlo method as a numerical modelling tool to incorporate uncertainties in the measured physical/chemical/ biochemical data is demonstrated as well. A list of studies conducted with different chemicals alone or in combination with various biocides to mitigate biogenic souring provides an overview of potential inhibitors as well as possible applications. Furthermore, the results of static and dynamic inhibition tests using molybdate are presented in more detail due to its promising mitigation ability. Finally, a three-step workflow for the risk assessment of biogenic souring and its possible mitigation is presented and discussed.

Second-level hospitals face peculiarities that hinder the implementation of the hearing rescreening protocol, which are not uncommon in other settings. This study analyzes the hearing rescreening process in this kind of hospital. A total of 1130 individuals were included. In this cohort, 61.07% were newborns in the hospital who failed their first otoemission test after birth (n=679) or were unable to have the test performed (n=11), then being referred to outpatient clinic. The remaining 38.93% were individuals who were born in another hospital with their first test conducted in the outpatient clinic (n=440). A high amount of rescreenings were made outside the recommended time frame, mainly in children referred from another hospital. There was a high rate of lost to follow-up especially with otolaryngologist referrals. Neonatal Hearing screening in second level hospitals is difficult because of the staffing and time constraints. This results in longer than recommended turnaround times and interferes with the timely detection of hearing loss. This is particularly serious in outpatients. Referral of children with impaired screening to out-of-town centers leads to unacceptable loss of follow-up. A legislative support for all these rescreening issues is necessary. We discuss these findings and propose some solutions.

This paper presents a methodology based on deep learning models and metaheuristic algorithms for the optimization of airfoils for the design of aircraft wings with large endurance. The use of AZTLI-NN (a neural network with an architecture composed of a multilayer perceptron and a variational autoencoder) is implemented for the prediction of graphs of the aerodynamic coefficients of the airfoil as a function of the angle of attack. This neural network presents good predictions of the aerodynamic coefficients, similar to the coefficients obtained with computational fluid dynamics simulations. AZTLI-NN in combination of metaheuristic algorithms and the CST profile parameterization method show excellent performance in single-objective and multi-objective profile optimization tasks.

The catalytic parameters describing enzyme catalysis are discussed in the context of the design of de novo enzymes. It is shown that high values of the catalytic efficiency may in some cases reflect tight substrate binding and lead to an immediate levelling-off of rates to reach a low plateau, an undesirable scenario for many industrial applications. It is argued that increasing the catalytic rate constant should be a main target in de novo enzyme engineering.

Security in IoT systems is extremely important, as an intrusion into an IoT device or network can affect not only our domestic lives, but also industrial assets, with the potential to cause enormous damage. We discuss IoT security issues as defined by the OWASP Foundation, focusing on network related aspects. After a brief description of SDN in general and OpenFlow in particular, we discuss how SDN technologies can greatly help in designing and deploying more secure IoT networks by enhancing the cryptographic capabilities of devices, isolating devices or networks, blocking access to unwanted services, redirecting traffic to deep inspection systems, monitoring packet flows and devices, etc. These capabilities can be implemented using open-source OpenFlow controllers such as Faucet.

Abstract Chaga´s disease caused by Trypanosoma cruzi infections is included in the group of neglected diseases, and efforts to develop new therapeutic or immunoprevention approaches have not been successful. After the publication of the T. cruzi genome, the number of molecular and biochemical studies on this parasite have increased considerably, many of which are focused on families of variant-surface-proteins, especially the trans-sialidases, mucins and mucin-associated proteins. The disperse gene protein 1 family (DGF-1) is one of the most abundant families in the T. cruzi genome, however, the large gene size, high copy numbers, and low antibody titers detected in infected humans make it an unattractive study target. Here, we argue that the DGF-1 gene family although not being the most obvious participant of the host-parasite immunological gamble, where T. cruzi appears to have the upper hand, it may play an important role in more basic host-parasite interactions that deserve further examination.

Congenital deafness is a major pediatric problem, affecting about 1.5-3 per 1000 newborns. The early treatment through cochlear implantation and auditory rehabilitation has been a historic milestone. Early diagnosis of congenital deafness is an essential requirement to obtain the best results, which is achieved through neonatal screening, a diagnostic practice that we began systematically at the Hospital Clínico in Valencia (Spain) 30 years ago.

Landscape restoration activities must be conducted through a transdisciplinary process, integrating social, economic, environmental, and governance aspects. Combining visions from the natural and social sciences is a challenge in highly complex territories, where unique ecosystem characteristics, economic processes, stakeholders of diverse nature, and different normativity converge. The harmonization of multiple techniques, such as multicriteria spatial analysis, expert knowledge elicitation, and social mapping, allows for an approach to defining landscape restoration areas in complex regions. This paper employs multiple techniques to define ecosystem restoration areas in a complex Colombian Andes landscape, integrating ecological and social components for sustainable development. We observed that areas of high and very high feasibility for ecological restoration, encompassing 179.5 hectares (4.84% of the study area), are predominantly located near primary forests. Although some areas have low feasibility for conservation processes, they should not be disregarded as they still require protection. Landowners prioritize watershed and soil restoration as the most important landscape restoration activity due to their interest in improving water-related ecosystem services. This proposal enables the identification of areas with higher restoration potential at the property level, facilitating prioritization and investment allocation for future implementation.

Finding an optimal combination of features and classifier is still an open problem in the development of automatic heartbeat classification systems, especially when applications that involve resource-constrained devices are considered. In this paper, a novel study of the selection of informative features and the use of a random forest classifier while following the recommendations of the Association for the Advancement of Medical Instrumentation (AAMI) and an inter-patient division of datasets is presented. Features were selected using a filter method based on the mutual information ranking criterion on the training set. Results showed that normalized R-R intervals and features relative to the width of the QRS complex are the most discriminative among those considered. The best results achieved on the MIT-BIH Arrhythmia Database were an overall accuracy of 96.14% and F1-scores of 97.97%, 73.06%, and 90.85% in the classification of normal beats, supraventricular ectopic beats, and ventricular ectopic beats respectively. In comparison with other state of the art approaches tested under similar constraints, this work represents one of the highest performances reported to date while relying on a very small feature vector.