District University of Bogotá

To better understand the anaerobic digestion process, models can be made based on already performed fermentations, however, these models are limited in the literature. In this contribution, a model was developed based on the modified Hill model, which can predict the production of volatile fatty acids. The model used eight differential equations reported by Haugen who is based on the modified Hill model and four state variables, using MATLAB. This model can predict the production of volatile fatty acids in both semi-continuous and batch processes, using substrates digested sludge and primary sludge from a Wastewater Treatment Plant under different conditions such as organic load, temperature, pH, and hydraulic retention time. The deviation between the experiments performed and the model developed was less than ± 9.1%, demonstrating this model’s accuracy and robustness. Furthermore, the statistical analysis showed that there were no significant differences between the fermentations and the simulation, verifying the null hypothesis. The developed model identified a stable and optimal VFA-generating loading rate from experimental data. Graphical Abstract

In this article, we provide a description of the Auslander–Reiten quiver for certain posets endowed with an involution, which we denote as types $\mathfrak {U}_n$ U n and $\mathfrak {U}_\infty$ U ∞ . These posets appear in Zavadskij’s Differentiation III (Can Math Soc Conf Proc 11:299–323, 1991). Our approach follows the classical Auslander–Reiten theory developed by Auslander, Reiten, and Smalø (Representation Theory of Artin Algebras. Cambridge Studies in Advanced Mathematics, UK, 1992). To this end, we establish a natural exact structure for the category of representations of a partially ordered set with an involution, and subsequently delineate the projective and injective representations.

The infratribe Neosatyriti is a section of the entirely Neotropical subtribe Pronophilina, accounting for 57 species distributed from southern Patagonia to the Andes of northern Peru, and along the Atlantic coast, with the highest diversity in central Chile. They are found in two main types of habitats, i.e. puna, pampas and subantarctic grasslands, and Valdivian forests and Chilean matorral, from sea level to nearly 5000 m above sea level. We propose a phylogenetic hypothesis of the infratribe based on molecular data obtained by target enrichment (TE) of 621 nuclear loci, totalling 248,373 base pairs, from 53 species of this infratribe and 12 outgroups. Our analysis confirms that Neosatyriti is monophyletic with full support. Based on these results, we propose eight new combinations and two status reinstatements. Molecular data are congruent with morphological characters except for Homoeonympha which appears to be paraphyletic, thus almost all the genera described originally by L. Herrera, K. Hayward and W. Heimlich in the Twentieth century based only on morphological characters are confirmed as valid, except for Haywardella that is synonymised with Pampasatyrus. Neosatyriti diverged from other Pronophilina some 23 Ma and split into two major lineages some 20 Ma. Our reconstructions do not indicate a single area of origin, rather a multisource origin, but they suggest the Neosatyriti originated in the lowlands, and that their ancestral plants were non-bambusoid grasses. Major divergence of the infratribe started some 12–11 Ma when it split into the ‘Neomaenas clade’ (9 genera), the ‘Pampasatyrus clade’ (4 genera) and the ‘Neosatyrus clade’ (5 genera). The next main radiation took place some 7–5 Ma with the switch to bamboo host plants and the colonisation of Valdivian forests. The final dispersal of the tribe was associated with the colonisation of Mata Atlantica some 6–5 Ma, and high Andean puna in Peru in the Early Pleistocene. ZooBank: urn:lsid:zoobank.org:pub:29A961D1-99EF-465C-87E7-FB5B3570E3AE

Soil fauna had little influence on decay rates, but the effect varied by species. Soil fauna richness and abundance did not influence decomposition environment. Body size traits of soil fauna were unrelated to decomposition environment. Limited macrofauna presence explained the lack of soil fauna’s effect on decay rates. Macrofauna contribution to decomposition had weak effects on succession. Recent studies and global meta-analyses suggest that soil fauna is a key driver of litter decomposition. However, most research has focused on lowland ecosystems, leaving tropical mountain regions underexplored. Our study investigated the influence of the taxonomic and functional structure of soil fauna communities on litter decomposition in successional upper Andean tropical forests. We conducted two reciprocal translocation experiments: one examining 15 litter species (2 525 litterbags) and another analyzing macrofauna exclusion (336 litterbags). We also performed extensive soil fauna sampling across four climatic seasons (6 999 individuals) and measured body size traits for 93% of the morphospecies. We analyzed the role of soil fauna attributes (richness, abundance, body size) on litter decomposition at the species and ecosystem levels in four sites of successional upper Andean tropical forests in Colombia. Our findings indicated that soil fauna has little influence on decomposition, yet the effect varies by species, suggesting specific affinities between soil fauna and litter substrates. The lack of influence of soil fauna richness, abundance, and body size can be attributed to the dominance of small-sized fauna in upper Andean tropical forests. The contribution of soil macrofauna to decomposition was higher in mature forests, but this effect was weak over time. Further studies should explore indirect effects and microbial interactions to better understand soil fauna’s role in decomposition. Our study highlights that the influence of soil fauna on decay rates is context-dependent and should not be generalized across all ecosystems.

This paper presents the development of a temperature model, based on the energy balance of a semi-continuous reactor consisting of 3 stainless steel digesters of 6L each, operating at temperatures from 25 to 75 °C, with stirrer, gas sampling points and pH and temperature control panels; in addition, the reactors depend on the ambient temperature and the input power. This model is intended to predict the thermal behaviour of the reactor. The variables that are not independent are estimated from three methods, the method of least squares with a static model, the method of least squares with a dynamic model and the method of nonlinear least squares with dynamic model and additional delay, the last one presents a new dynamic with respect to the original model. For the estimation of variables and subsequent comparison between methods, data were taken from the reactor in operation for 4 days. As a result, it was possible to estimate the reactor temperature with a maximum error of approximately one degree Celsius, where it is obtained that the best model is the least squares method with a static model. This pilot-scale work generates contributions to the challenge of improving energy efficiency in biogas production models, or value-added products such as volatile fatty acids, through Anaerobic Digestion (AD) considering that this is one of the conditions to be evaluated in industrial scale-up processes.

The avocado seed is a major waste generated by the avocado agroindustry in different countries. This waste can be valorized by producing biofuels and other products through a circular economy approach. In this work, the Kissinger–Akahira–Sunose (KAS) and Ozawa-Flynn Wall (OFW) isoconversional methods were used to estimate the activation energy of pyrolysis, which ranged from 24.17 to 226.34 kJ/mol. Additionally, avocado seeds were pyrolyzed in laboratory equipment to generate biochar, gas, and bio-oil. Bio-oil was obtained with a yield of 4% and a maximum caloric value of 21.641 kJ/kg, with a high hydrocarbon content. Biochar (37.5 wt.%) was also obtained, which gained energy and activated carbon. Gas is significant in the pyrolysis process, with 60% productivity. Three cases of pyrolysis processes were simulated, which presented better experimental performance related to biochar and bio-oil yields. These cases were assessed via a sensitivity analysis of the economic component, where the economic margin of both pyrolytic products is positive for any sale price. In the minimum price of biochar, the economic margin was approximately 2%, whereas in the maximum price, the profit was approximately 60%. For the case of bio-oil, the maximum profit was approximately 35%. This research demonstrated the high potential of rapid pyrolysis of avocado seed residues for obtaining bio-oil and biochar fuels with high energy values and promoting a circular economy.

Despite a large body of research upon language teachers received technical knowledge, only a few studies have accounted for their own understanding of their self‐as‐teacher since the beginning of the new millennium. The dichotomy between the technical and human dimensions that it implies for education is addressed as perpetuated by neoliberal ideologies. This article does it by studying three language educators' problematizing of top‐down identity‐shaping neoliberal tenets of quality assurance and competitiveness in the market that brought about their reflexivity upon their own identities as English language (EL) teachers. The three EL teachers' introspection and verbalization of their stories and experiences when complying with institutional demands shed light upon their counter‐discourses contesting neoliberal‐laden pervading discourses. It served to add understanding about the (re)construction of their identities in a dialogical and reflexive space created for the study. Their stories were collected through narrative interviews which were later transcribed and analyzed from a thematic and ecological framework. Findings suggest that neoliberal forces over EL teachers' agency incite their decisions and actions to tackle those certainties and uncertainties present in the human–technical dichotomy of English language teaching (ELT). Such a dichotomy leads EL teachers to deal with the myths of homogenization, idealization, and excellence typically present in foreign language schools' marketization practices.

Introduction The software industry has rapidly evolved with high performance. This is owing to the implementation of good programming practices and architectures that make it scalable and adaptable. Therefore, a strong incentive is required to develop the processes that initiate this project. Method We aimed to provide a platform that streamlines the development process and connects planning, structuring, and development. Specifically, we developed a system that employs computer vision, deep learning, and MDA to generate source code from the diagrams describing the system and the respective study cases, thereby providing solutions to the proposed problems. Results and discussion The results demonstrate the effectiveness of employing computer vision and deep learning techniques to process images and extract relevant information. The infrastructure is designed based on a modular approach employing Celery and Redis, enabling the system to manage asynchronous tasks efficiently. The implementation of image recognition, text analysis, and neural network construction yields promising outcomes in generating source code from diagrams. Despite some challenges related to hardware limitations during the training of the neural network, the system successfully interprets the diagrams and produces artifacts using the MDA approach. Plugins and DSLs enhance flexibility by supporting various programming languages and automating code deployment on platforms such as GitHub and Heroku.

Theobroma grandiflorum (copoazu) is a plant native to South America, widely cultivated in countries within the Amazon region. Its unique phytochemical composition imparts distinctive organoleptic properties, making it an exotic fruit. In this study, headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–mass spectrometry (GC-MS) was used to identify the volatile organic compounds (VOCs) produced by copoazu. The optimal conditions for sample pretreatment were first determined using a Design of Experiments (DoE) approach. Analysis of the volatile profiles enabled the identification of 96 copoazu VOCs across three ripening stages. Of these, 79 VOCs were classified into chemical compound families using spectral correlation analysis across various libraries and databases, as well as molecular network analysis. Additionally, a volatilomic analysis was conducted to examine the changes in VOCs throughout the ripening process. Molecular network analysis showed that the VOCs emitted by the fruit are linked to the interconversion of compounds, which can be observed through the study of the metabolic pathways. These findings provide a comprehensive analysis of the copoazu volatilome, providing valuable insights into the organoleptic characteristics of this Amazonian fruit. Esters and terpenes such as α-terpineol, trans-4-methoxythujane, linalool, 2-methylbutyl butanoate, 3-methylbut-2-enoic acid, 2-methylpentyl ester, and 2-methylpropyl hexanoate were identified as potential biomarkers associated with the copoazu ripening process.

Two additional species of Sticta are described as new to science based on material from Bolivia and Peru and supported by phylogenetic analysis of the fungal ITS barcoding marker. The two new species represent lineages within clade I on the global Sticta phylogeny. Sticta flakusiorum Ossowska, B. Moncada & Lücking is a species in the S. humboldtii morphodeme and is characterized by lobes partly to entirely covered with white hairs, also covering the margins of submarginal and laminal apothecia, and the scabrid basal membrane of cyphellae, which is white to yellow, or partly brown, and when yellow K+ purple. The taxon was discovered at a single locality in Bolivia, but it is closely related to a potentially new Sticta species from Peru, which is here left undescribed. The other new species, S. kukwae Ossowska, Magain & Sérus., belongs to the S. weigelii morphodeme. It has lobes with sinuous margins and dark, palmate to corymbose phyllidia. It was collected at several locations in Peru and a single locality in Bolivia.

Resumen La incidencia de la interacción social con el otro en el desarrollo del pensamiento algebraico de los estudiantes es un tema de interés actual para la investigación en educación matemática. Estudios en el campo han identificado diferentes formas de interacción social en el aula y sugieren profundizar en el problema sobre cómo estas inciden en el desarrollo del pensamiento matemático de los estudiantes. En este sentido y considerando la ética como la manera de relacionarse con el otro, el presente artículo aborda el análisis de la incidencia de los vectores de una ética de orientación comunitaria en los procesos de generalización que elaboran estudiantes de grado quinto de primaria, con edades de 10 y 11 años, de un colegio de Bogotá, Colombia. El estudio emplea como marco teórico la teoría de objetivación, como marco metodológico el análisis multimodal, y aporta evidencias empíricas que permiten establecer la incidencia de estos vectores en los procesos de generalización que realizan los estudiantes y en el tránsito a generalizaciones de nivel superior.

Drawing inspiration from online question-and-answer communities often regarded as embodiments of Collective Intelligence (CI), this study investigates the dynamics of reputation-driven and distributed network interactions in multi-agent systems as a model for problem-solving in global optimisation. We explore the interplay among diverse participants, including Solvers motivated by reputation and Users seeking net benefits, recognising its critical role in fostering success within these communities. Our study translates the principles of CI inherent in these interactions into a novel agent-based search algorithm for unconstrained optimisation of continuous-valued cost functions. Empirical testing across a suite of established benchmark problems allows a comparative analysis of its performance against alternative agent-based methodologies. These findings underscore the algorithm’s advantages across diverse optimisation 2D landscapes, highlighting the potential of the CI framework as a promising avenue in metaheuristic research. They illustrate how the interaction between individual actors and the collective, favours the emergence of global solutions in unknown environments, mirroring similar emergent phenomena observed in social organisations.

This study investigated the effects of multiple laser sintering (LS) cycles on a polyamide 12 powder mixture of 70% recycled material and 30% virgin polymer. This research aimed to understand how repeated LS processing influences this specific powder mixture’s thermal and structural properties, which is crucial for optimising its performance in additive manufacturing applications. A thermal analysis revealed significant changes in the thermal behaviour of the powder over successive build cycles. Specifically, there was an observed increase in both the melting temperature and the crystallinity of the powder, alongside a notable decrease in the crystallisation temperature. These alterations suggest that the repeated LS cycles affect the thermal profiles and potentially enhance the material’s stability and usability in additive manufacturing processes. Additionally, a particle size distribution analysis indicated statistically significant differences between the initial and post-sintering states of the powder. These differences are significant as they can influence factors such as flowability and packing density, which are critical for the efficiency of additive manufacturing applications. Microscopic observations further revealed a strong correlation between the crystal morphologies and particle shapes, indicating that the structural changes occurring during processing are inter-related. The relationship underscores the importance of understanding microstructural evolution and the mechanical properties of the final printed products. These findings provide crucial insights into the microstructural evolution and thermal behaviour of recycled PA12 powder during multiple LS processing cycles. This study aids in developing practical strategies for sustainable and efficient powder recycling within the realm of additive manufacturing. By examining the intricate dynamics at play, the research opens avenues for enhancing the performance and environmental sustainability of 3D printing technologies, making them more accessible for various industrial applications.

This research investigates the effectiveness of four metaheuristic algorithms, the Population-Based Genetic Algorithm, Particle Swarm Optimization, JAYA, and Generalized Normal Distribution Optimizer, for managing the energy production of wind-based distributed generators (DGs). The aim is to reduce operational costs in a 33-node microgrid (MG) operating under both connected and isolated configurations. The study seeks to identify the most efficient algorithm for minimizing operational expenses in distributed generation systems, specifically in terms of energy production and purchasing costs, as well as the maintenance costs of DGs. Due to limited statistical validation and unrealistic operational constraints in previous studies, we propose a novel framework that offers a robust, reproducible solution for optimizing the management of wind-based distributed generators in microgrids. Through 100 independent trials for each algorithm and configuration, rigorous statistical analyses are conducted, including ANOVA and Tukey’s post hoc test, to assess performance consistency and the significance of cost reduction outcomes across algorithms. The results indicate that the PGA demonstrates superior cost efficiency and stability, particularly in the connected MG configuration.

Morphometric traits of a host have been used recently in disease ecology for a deeper understanding of the connection between phenotype and transmission rates. The common vampire bat, Desmodus rotundus , is the main reservoir of rabies in Latin America, one of the most lethal zoonotic diseases in the world. Comprehension of morphological variation in D. rotundus is insufficient, contradictory, and inconclusive. Due to this inconsistency, we explored sexual dimorphism in D. rotundus by combining different measures to provide new knowledge that can contribute to the control of rabies. As a result, our study provides evidence of sexual dimorphism in D. rotundus with females generally larger than males in body and wing measurements. The statistical, as well as the principal components, and clusters analysis, confirm morphological differences between females and males, without observing a complete separation between the sexes, possibly due to environmental factors that change the specimens' conditions or limitations with access to measures. Understanding the sexual dimorphism of the main transmitter of wild rabies in South America is essential since morphological variations between sexes could influence both the use of the habitat and the dispersion capacity of the bats, which are relevant to the epidemiology of rabies. Because our data originated primarily from lowland areas, we are unable to rule out the effects of elevation on sex dimorphism. Given the importance of rabies for global public health, investigating the morphological and behavioral aspects of rabies reservoirs could help us better understand how ecological aspects influence disease spread.

This article proposes an efficient energy management system for optimally scheduling distributed energy resources based on photovoltaic static synchronous compensators (PV-STATCOMs) in medium-voltage distribution networks. The complete nonlinear programming (NLP) model is reformulated as a semi-definite programming (SDP) relaxation in the complex domain. The key feature of our approximation lies in utilizing a set of Hermitian semi-definite matrices $\mathbb {X}_{n,n,h}$, which allows transforming the NLP model from $\mathbb {C}^{n}$ into a linear programming one in the space of complex square matrices defined in $\mathbb {C}^{n\times n}$. The IEEE 33-bus grid was selected as a test feeder in order to evaluate the performance of the proposed relaxation through numerical experiments. Two objective functions are considered: (i) the minimization of the energy purchasing costs at the substation terminals and (ii) the minimization of the expected daily energy losses. The results demonstrate the effectiveness and robustness of our proposed SDP relaxation approach.

In this manuscript, we propose a simplified mathematical model based on the heat transfer laws to predict the temperature profiles of a liquid controlled by a simple thermostat. The model result in a set of linear ordinary differential equations ODEs with forcing which turn on and off at a priori unknown times ${\mathcal {T}}_M=\left\{ \zeta _0,\zeta _1,\ldots ,\zeta _M\right\}$. The pth switch-time $\zeta _p\in {\mathcal {T}}_p$ is calculated from the zeros of a function ${\mathcal {Q}}(\chi )={\mathcal {Q}}(\chi ;\zeta _1,\ldots ,\zeta _{p-1})$ coming from analytical solutions of the system depending on the previous times $\zeta _1,\ldots ,\zeta _{p-1}$. The mathematical problem can be solved by using standard techniques for solving ODEs once ${\mathcal {T}}_M$ is calculated by M-successive iterations of the conditional expression ${\mathcal {Q}}(\chi =\zeta _p)=0$ and the Newton–Raphson method. We provide analytical expressions for the temperature as a function of time and ${\mathcal {T}}_M$ considering direct (DC) and alternate (AC) feeding voltages. We solve the system using this numerical-analytical approach and compare it with the results of the 4th Runge–Kutta method finding a good agreement between both methods.