Natural Transformation Research Articles

On the Differentiation of Integrals in Measure Spaces Along Filters: II

Let X be a complete measure space of finite measure. The Lebesgue transform of an integrable function f on X encodes the collection of all the mean-values of f on all measurable subsets of X of positive measure. In the problem of the differentiation of integrals, one seeks to recapture f from its Lebesgue transform. In previous work we showed that, in all known results, f may be recaptured from its Lebesgue transform by means of a limiting process associated to an appropriate family of filters defined on the collection A\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\,\\mathrm{{\\mathcal {A}}}\\,}}$$\\end{document} of all measurable subsets of X of positive measure. The first result of the present work is that the existence of such a limiting process is equivalent to the existence of a Von Neumann-Maharam lifting of X. In the second result of this work we provide an independent argument that shows that the recourse to filters is a necessary consequence of the requirement that the process of recapturing f from its mean-values is associated to a natural transformation, in the sense of category theory. This result essentially follows from the Yoneda lemma. As far as we know, this is the first instance of a significant interaction between category theory and the problem of the differentiation of integrals. In the Appendix we have proved, in a precise sense, that natural transformations fall within the general concept of homomorphism. As far as we know, this is a novel conclusion: Although it is often said that natural transformations are homomorphisms of functors, this statement appears to be presented as a mere analogy, not in a precise technical sense. In order to achieve this result, we had to bring to the foreground a notion that is implicit in the subject but has remained hidden in the background, i.e., that of partial magma.

Simulation of temperature rise in low voltage winding of natural oil circulation transformer and analysis of oil flow heat dissipation

Abstract The heat dissipation performance of an oil-immersed transformer is the key to its stable operation. Winding loss is a crucial part of transformer heat loss, and winding heat dissipation greatly influences the rise in transformer temperature. In this paper, depending on the finite element method, the magnetic field distribution of a 66 MVA (225/26.4 kV) natural oil circulation transformer is analyzed, and the DC and eddy current losses of the low voltage winding are calculated. Based on the finite volume method, the temperature field distribution of the low-voltage winding is calculated, and the heat flux distribution of the contact surface between the disc insulation paper and the oil flow is obtained. It is found that there are transition points and extreme points between the upper and lower surface of the disc and the inner and outer surface of the disc, and the heat flux on the upper and lower surface of the disc conductor has obvious alternating oscillation. This study provides direction for further analysis and understanding of the heat dissipation mechanism and structural design of natural oil circulation transformers.

Clinical features and associated factors of impaired ventilatory efficiency: findings from the ECOPD study in China

BackgroundImpaired ventilatory efficiency during exercise is a predictor of mortality in chronic obstructive pulmonary disease. However, little is known about the clinical features and associated factors of impaired ventilatory efficiency...

Natural and Climatic Transformation of the Kakhovka Reservoir after the Destruction of the Dam

Natural and Climatic Transformation of the Kakhovka Reservoir after the Destruction of the Dam

The role of cytolethal distending toxin in Glaesserella parasuis JS0135 strain infection: Cytotoxicity, phagocytic resistance and pathogenicity

Glaesserella parasuis is an important porcine pathogen that commonly colonizes the upper respiratory tract of pigs and is prone to causing Glässer’s disease under complex conditions. As yet, the disease has led to serious economic losses to the swine industry worldwide. Studies so far have found that several virulence factors are associated with the pathogenicity of G. parasuis, but the pathogenic mechanism is still not fully understood. Cytolethal distending toxin (CDT), a potential virulence factor in G. parasuis, is involved in cytotoxicity, serum resistance, adherence to and invasion of host cells in vitro. Here, to further investigate the pathogenic role of CDT during G. parasuis infection in vitro and in vivo, a double cdt1 and cdt2 deletion mutant (Δcdt1Δcdt2) without selectable marker was first generated in G. parasuis JS0135 strain by continuous natural transformations and replica plating. Morphological observation and lactate dehydrogenase assay showed that the Δcdt1Δcdt2 mutant was defective in cytotoxicity. Additionally, the Δcdt1Δcdt2 mutant was more susceptible to phagocytosis caused by 3D4/2 macrophages compared to the wild-type JS0135 strain. Moreover, by focusing on clinical signs, necropsy, bacterial recovery and pathological observation, we found that the deletion of cdt1 and cdt2 genes led to a significant attenuation of virulence in G. parasuis. Taken together, these findings suggest that as an important virulence factor, CDT can significantly affect the pathogenicity of G. parasuis.

Categor´ıas del An´alisis Funcional

The objective of this article is to categorically focus on some aspects of Functional Analysis, aiming to present a high-level methodology for research and teaching. In section 1 the notions of category and subcategory are given; The Identification Convention and the Principle of Duality are stated; Some categories are presented and important properties of their objects and morphisms are stated. In section 2, functors and natural transformations are studied, showing their importance through examples that connect algebra and topology. In section 3 the important notions of limit of a functor and of adjunction of functors are given, and some examples are considered.

PROSPECTS AND LIMITS OF ARTIFICIAL INTELLIGENCE IN THE CONTEXT OF NATURAL INTELLIGENCE (philosophical and methodological aspects) / ПЕРСПЕКТИВЫ И ПРЕДЕЛЫ ВОЗМОЖНОСТЕЙ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В КОНТЕКСТЕ ЕСТЕСТВЕННОГО ИНТЕЛЛЕКТА (философско-методологические аспекты)

Artificial intelligence is characterized as non-living intelligence, although attempts are being made to pass from the principles of biological neural networks to artificial living neural networks. The human brain is assumed to be a complex system of physicochemical neurophysiological biochemical integration of neural networks, which encodes a specific type of biological information, cognitive information. Intelligence is a specific quality of the process of thinking as an expression based on the neurophysiological mechanism of prediction. Nowadays, people more and more often speak about the anthropological, axiological crisis, modification and transformation of human nature, the creation of biological hybrids that compete with natural ones. It will hardly be possible to formalize the complexities of the human brain and mind into digital code in artificial intelligence.

Decarbonization frameworks to industrial-scale ammonia production: Techno-economic and environmental implications

Ammonia production traditionally relies on steam methane reforming (SMR), but it emits carbon and harms the environment. To address decarbonization frameworks of industrial-scale ammonia production process, a 100,000-ton ammonia manufacturing plant is presented using green ammonia synthesis methods. This study presents two promising hydrogen production methods for ammonia production, utilizing water electrolysis as scenario 1 and biomass gasification as scenario 2, while nitrogen is supplied using a cryogenic air separation unit (CASU). The techno-economic analysis shows that the ammonia production via SMR as the base case has lower total costs than Scenarios 1 and 2 due to not using green electricity. Through the environmental impact assessment of climate change, ozone depletion, terrestrial ecotoxicity, and natural land transformation, it is shown that Scenario 1 has lower impacts than the base case and Scenario 2 due to using green electricity. It is noted that the base case and Scenario 1 ensure the lowest production cost and environmental impacts, respectively, and Scenario 2 is the best balance between the economy and the environment.

Identification of subcomplexes and protein-protein interactions in the DNA transporter of Thermus thermophilus HB27

The natural transformation system of the thermophilic bacterium Thermus thermophilus comprises at least 16 competence proteins. Recently we found that the outer membrane (OM) competence protein PilW interacts with the secretin channel, which guides type IV pili (T4P) and potential DNA transporter pseudopili through the OM. Here we have used biochemical techniques to study the interactions of cytoplasmic, inner membrane (IM) and OM components of the DNA transporter in T. thermophilus. We report that PilW is part of a heteropolymeric complex comprising of the cytoplasmic PilM protein, IM proteins PilN, PilO, PilC and the secretin PilQ. Co-purification studies revealed that PilO directly interacts with PilW. In vitro affinity co-purification studies using His-tagged PilC led to the detection of PilC-, PilW-, PilN- and PilO-containing complexes. PilO was identified as direct interaction partner of the polytopic IM protein PilC. PilC was also found to directly interact with the cytoplasmic T4P disassembly ATPase PilT1 thereby triggering PilT1 ATPase activity. This, together with the detection of heteropolymeric PilC complexes which contain PilT1 and the pilins PilA2, PilA4 and PilA5 is in line with the hypothesis that PilC connects the depolymerization ATPase to the base of the pili possibly allowing energy transduction for disassembly of the pilins.

Anadromous sturgeon fish of the Azov Sea under conditions of natural and anthropogenic transformations of the water ecosystem

The aim: assessment of the state of populations of anadromous sturgeon in the Sea of Azov, the efficiency of their reproduction and the possibility for the existence of populations in the medium term until 2030–2040. Methods: the calculation of the biomass and population size of sturgeon in the Sea of Azov was carried out using the direct counting method and a modified cohort solution of the Baranov equation. 18and 25-meter bottom trawls were used as standard fishing gear. The assessment of the number of juvenile sturgeon in the Don River was carried out with 3and 2-meter beam-trawls. Molecular genetic methods for the analysis of microsatellite loci and sequencing of a fragment of the control region of mitochondrial DNA were used.Novelty: materials are presented on natural reproduction of sturgeon in the Don River after flow regulation, and the rate of decline in the survival rate of generations of Russian sturgeon and stellate sturgeon under the influence of illegal fishing is shown. Based on the results of a study of the genotypes of Russian sturgeon individuals, migrations sturgeon from Azov to the Black Sea, as well as Black Sea populations to the Sea of Azov, were confirmed.Results: an analysis of the dynamics and current state of anadromous sturgeon in the Sea of Azov is presented under the conditions of anthropogenic transformation of their habitat, loss of natural reproduction and climate-related fluctuations in the salinity of the sea waters. A retrospective overview of their commercial use from the mid-19th century to the present is given. The prospects for restoring commercial stocks of sturgeon fish are considered.Practical significance: the possibility of restoring commercial stocks of sturgeon in modern conditions is shown by increasing the number of released juveniles and increasing the effectiveness of fish conservation measures to a level of more than 90 thousand tons and creating an commercial population of sturgeon in the Sea of Azov.

The Universality of Functions in the Sciences at Large and in Computing

Universality of a concept here means wide conceptual and practical usefulness in mathematics and applications. The function concept owes its universality to simplicity, generality, and powerful algebraic properties. Advantages proven in the sciences at large significantly benefit computing science as well. Universality critically depends on the definitional choices. The first half of this article shows that a “function” in the sense prevalent throughout the sciences, namely, as fully specified by its domain and its values , entails the characteristics that most contribute to universality. This link is clarified by some less well-understood aspects, including the role of function types as partial specifications, the ramifications of having composition defined for any pair of functions, and unification by capturing various notions not commonly seen as functions. Simple but representative examples are given in diverse areas, mostly computing. When a codomain appears at all in basic textbooks, it mostly involves a self-contradicting definition, corrected by the labeled function variant. Either way, it severely reduces universality, especially for composition. Yet, the axiomatization of category theory common in theoretical computing science offers no other choice. The second half explores how waiving one axiom generalizes category theory to include a wider variety of concepts, primarily the conventional function variant. It is also shown how this can be done unobtrusively for typical categorical notions, such as products, coproducts, functors, natural transformations, adjunctions, Galois connections, and auxiliary concepts, illustrated by example definitions and technical comments. Allowing the familiar function variant renders category theory more appealing to a wider group of scientists. A lesson for mathematics in general is Rogaway’s maxim: “Your definitional choices should be justified!”.

Half-metallic behavior in rare earth metal (Sm, Gd) co-doped zigzag Gallium Phosphide nanoribbons

Using first-principle calculations, we have studied the structural and electronic properties of the Gallium Phosphide (GaP) nanoribbon doped with rare earth (RE) metal elements. The substitution of Ga and P atoms with RE leads to the structural deformation in zigzag GaP nanoribbon. For every nanostructure under study, the binding energy (Eb), density of states (DOS), and electronic band structures have been computed. The bare and pristine undoped GaP show non-magnetic behavior. The bare z-GaPNR shows metallic nature while the pristine z-GaPNR exhibits band gap of 2.44 eV with indirect characteristics. With Samarium (Sm) and Gadolinium (Gd) doping in z-GaPNR, a transformation of the semiconducting nature of z-GaPNRs turns to half metallic one. The transport properties show that half-metal ferromagnetic behavior with 92%–98% spin polarization at the Fermi level is produced by RE (Gd, Sm) co-doped z-GaPNRs. The synergistic effect of the Gd and Sm impurities are seen to diminish energy band gaps. Conversely, we have the energy band gap in spin down energy levels results in semiconducting behavior, whereas in the spin up energy state, metallic behavior is observed. This could be caused by the 4f-states of the Sm and Gd dopants. Therefore, this work presents half-metallic (HM) properties for RE-doped z-GaPNRs. Our study depicts that the electrical, spin, and transport properties of z-GaPNRs could be altered magnificently by co-doping of Gd and Sm rare earth metals. Additionally, the current findings can be used to create a workable method of absolute fermi level shifting for spin energy levels, which is required for applications involving spintronic devices, spin filters, as well as for z-GaPNRs’ electrical characteristics modifications.

Natural transformation of Vibrio natriegens with large genetic cluster enables alginate assimilation for isopentenol production

Alginate is a major component of brown macroalgae, and its efficient utilization is critical for developing sustainable technologies. Vibrio natriegens is a fast-growing marine bacterium that has gained massive attention due to its potential as an alternative industrial chassis. However, V. natriegens cannot naturally metabolize alginate, limiting its usage in marine biomass conversion. In this study, V. natriegens was engineered to utilize marine biomass, kelp, as a carbon source. A total of 33.8 kb of the genetic cluster for alginate assimilation from Vibrio sp. dhg was integrated into V. natriegens by natural transformation. Engineered V. natriegens was further modified to produce 1.8 mg/L of isopentenol from 16 g/L of crude kelp powder. This study not only presents the very first case in which V. natriegens can be naturally transformed with large DNA fragments but also highlights the potential of this strain for converting marine biomass into valuable products.

Roe functors preserve homotopies

We show that coarse maps between countable metric spaces of bounded geometry induce natural transformations of sufficiently good endofunctors of C ∗ C^{*} -algebras and prove that this correspondence is invariant with respect to coarse homotopies.

Anthropogenic pollution may enhance natural transformation in water, favouring the spread of antibiotic resistance genes

Aquatic ecosystems are crucial in the antimicrobial resistance cycle. While intracellular DNA has been extensively studied to understand human activity's impact on antimicrobial resistance gene (ARG) dissemination, extracellular DNA is frequently overlooked. This study examines the effect of anthropogenic water pollution on microbial community diversity, the resistome, and ARG dissemination. We analyzed intracellular and extracellular DNA from wastewater treatment plant effluents and lake surface water by shotgun sequencing. We also conducted experiments to evaluate anthropogenic pollution's effect on transforming extracellular DNA (using Gfp-plasmids carrying ARGs) within a natural microbial community. Chemical analysis showed treated wastewater had higher anthropogenic pollution-related parameters than lake water. The richness of microbial community, antimicrobial resistome, and high-risk ARGs was greater in treated wastewaters than in lake waters both for intracellular and extracellular DNA. Except for the high-risk ARGs, richness was significantly higher in intracellular than in extracellular DNA. Several ARGs were associated with mobile genetic elements and located on plasmids. Furthermore, Gfp-plasmid transformation within a natural microbial community was enhanced by anthropogenic pollution levels. Our findings underscore anthropogenic pollution's pivotal role in shaping microbial communities and their antimicrobial resistome. Additionally, it may facilitate ARG dissemination through extracellular DNA plasmid uptake.

Teaching old dogs new tricks: genetic engineering methanogens.

Methanogenic archaea, which are integral to global carbon and nitrogen cycling, currently face challenges in genetic manipulation due to unique physiology and limited genetic tools. This review provides a survey of current and past developments in the genetic engineering of methanogens, including selection and counterselection markers, reporter systems, shuttle vectors, mutagenesis methods, markerless genetic exchange, and gene expression control. This review discusses genetic tools and emphasizes challenges tied to tool scarcity for specific methanogenic species. Mutagenesis techniques for methanogens, including physicochemical, transposon-mediated, liposome-mediated mutagenesis, and natural transformation, are outlined, along with achievements and challenges. Markerless genetic exchange strategies, such as homologous recombination and CRISPR/Cas-mediated genome editing, are also detailed. Finally, the review concludes by examining the control of gene expression in methanogens. The information presented underscores the urgent need for refined genetic tools in archaeal research. Despite historical challenges, recent advancements, notably CRISPR-based systems, hold promise for overcoming obstacles, with implications for global health, agriculture, climate change, and environmental engineering. This comprehensive review aims to bridge existing gaps in the literature, guiding future research in the expanding field of archaeal genetic engineering.

DNA binding is rate-limiting for natural transformation.

Bacteria take up environmental DNA using dynamic appendages called type IV pili (T4P) to elicit horizontal gene transfer in a process called natural transformation. Natural transformation is widespread amongst bacteria yet determining how different factors universally contribute to or limit this process across species has remained challenging. Here we show that Acinetobacter baylyi, the most naturally transformable species, is highly transformable due to its ability to robustly bind nonspecific DNA via a dedicated orphan minor pilin, FimT. We show that, compared to its homologues, A. baylyi FimT contains multiple positively charged residues that additively promote DNA binding efficiency. Expression of A. baylyi FimT in a closely related Acinetobacter pathogen is sufficient to substantially improve its capacity for natural transformation, demonstrating that T4P-DNA binding is a rate-limiting step in this process. These results demonstrate the importance of T4P-DNA binding efficiency in driving natural transformation, establishing a key factor limiting horizontal gene transfer.

Bacterial evolution in Biofiltration of drinking water treatment plant: Different response of phage and plasmid to varied water sources

Biofiltration in drinking water treatment (BDWT) are popular as it holds promise as an alternative to chemical treatments, yet our understanding of the key drivers and trends underlying bacterial evolution within this process remains limited. While plasmids and phages are recognized as the main vectors of horizontal gene transfer (HGT), their roles in shaping bacterial evolution in BDWT remain largely unknown. Here we leverage global metagenomic data to unravel the primary forces driving bacterial evolution in BDWT. Our results revealed that the primary vector of HGT varies depending on the type of source water (groundwater and surface water). Both plasmids and phages accelerated bacterial evolution in BDWT by enhancing genetic diversity within species, but they drove contrasting evolutionary trends in functional redundancy in different source water types. Specifically, trends towards and away from functional redundancy (indicated as gene-protein ratio) were observed in surface-water and groundwater biofilters, respectively. Virulent phages drove bacterial evolution through synergistic interactions with bacterial species capable of natural transformation and with certain natural compounds that disrupt bacterial cytoplasmic membranes. Genes relating to water purification (such as Mn(II)-oxidizing genes), microbial risks (antibiotic resistance genes), and chemical risk (polycyclic aromatic hydrocarbons) were enriched via HGT in BDWT, highlighting the necessity for heighted focus on these useful and risky objects. Overall, these discoveries enhance our understanding of bacterial evolution in BDWT and have implications for the optimization of water treatment strategies.

Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration

Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero JPY/kWh during peak RES production periods, substantially affecting transactions between electricity retailers and consumers. This paper introduces an innovative DAEPF framework employing a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model designed to predict day-ahead electricity prices in the Kyushu area of Japan. To mitigate the inherent uncertainties associated with neural networks, a novel ensemble learning approach is implemented to bolster the DAEPF model’s robustness and prediction accuracy. The CNN–LSTM model is verified to outperform a standalone LSTM model in both prediction accuracy and computation time. Additionally, applying a natural logarithm transformation to the target day-ahead electricity price as a pre-processing technique has proven necessary for higher prediction accuracy. A novel “policy-versus-policy” strategy is proposed to address the prediction problem of the zero prices, halving the computation time of the traditional two-stage method. The efficacy of incorporating a suite of multimodal features: areal day-ahead electricity price, day-ahead system electricity price, areal actual power generation, areal meteorological forecasts, calendar forecasts, alongside the rolling features of areal day-ahead electricity price, as explanatory variables to significantly enhance DAEPF accuracy has been validated. With the full integration of the proposed features, the CNN–LSTM ensemble model achieves its highest accuracy, reaching performance metrics of R2, MAE, and RMSE of 0.787, 1.936 JPY/kWh, and 2.630 JPY/kWh, respectively, during the test range from 1 March 2023 to 31 March 2023, underscoring the advantages of a comprehensive, multi-dimensional approach to DAEPF.

Fast prediction of temperature distributions in oil natural air natural transformers using proper orthogonal decomposition reduced‐order data‐driven modelling

Fast prediction of temperature distributions in oil natural air natural transformers using proper orthogonal decomposition reduced‐order data‐driven modelling