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ABSTRACT Nitrification is a core process in the global nitrogen (N) cycle mediated by ammonia-oxidizing microorganisms, including ammonia-oxidizing archaea (AOA) as a key player. Although much is known about AOA abundance and diversity across environments, the genetic drivers of the ecophysiological adaptations of the AOA are often less clearly defined. This is especially true for AOA within the genus Nitrosocosmicus, which have several unique physiological traits (e.g., high substrate tolerance, low substrate affinity, and large cell size). To better understand what separates the physiology of Nitrosocosmicus AOA, we performed comparative genomics with genomes from 39 cultured AOA, including five Nitrosocosmicus AOA. The absence of a canonical high-affinity type ammonium transporter and typical S-layer structural genes was found to be conserved across all Nitrosocosmicus AOA. In agreement, cryo-electron tomography confirmed the absence of a visible outermost S-layer structure, which has been observed in other AOA. In contrast to other AOA, the cryo-electron tomography highlighted the possibility that Nitrosocosmicus AOA may possess a glycoprotein or glycolipid-based glycocalyx cell covering outer layer. Together, the genomic, physiological, and metabolic properties revealed in this study provide insight into niche adaptation mechanisms and the overall ecophysiology of members of the Nitrosocosmicus clade in various terrestrial ecosystems.IMPORTANCENitrification is a vital process within the global biogeochemical nitrogen cycle but plays a significant role in the eutrophication of aquatic ecosystems and the production of the greenhouse gas nitrous oxide (N2O) from industrial agriculture ecosystems. While various types of ammonia-oxidizing microorganisms play a critical role in the N cycle, ammonia-oxidizing archaea (AOA) are often the most abundant nitrifiers in natural environments. Members of the genus Nitrosocosmicus are one of the prevalent AOA groups detected in undisturbed terrestrial ecosystems and have previously been reported to possess a range of physiological characteristics that set their physiology apart from other AOA species. This study provides significant progress in understanding these unique physiological traits and their genetic drivers. Our results highlight how physiological studies based on comparative genomics-driven hypotheses can contribute to understanding the unique niche of Nitrosocosmicus AOA

The enumeration of fuzzy subgroups is a complex problem. Several authors have computed results for special instances of groups. In this paper, we present a novel algorithm that is designed to enumerate the fuzzy subgroups of a finite group. This is achieved through the computation of maximal chains of subgroups. This approach is also useful for writing a program to compute the number of fuzzy subgroups. We provide further elucidation by computing the number of fuzzy subgroups of the groups $ Q_8 $ and $ D_8 $.

Multi-criteria group decision-making (MCGDM) approaches have a substantial effect on decision-making in a range of critical sectors, including science, business, and real-life research. These strategies also efficiently assist researchers in resolving challenges that may arise throughout their study activity. The current work's major purpose is to research and develop the combinative distance-based assessment (CODAS) approach by employing $ 2 $-tuple linguistic $ q $-rung picture fuzzy sets ($ 2 $TL$ q $-RPFSs) as a background. The CODAS technique computes the distances from the negative ideal solutions and ranks the alternatives in increasing order. To compute the normal weights of attributes, the entropy weighting information process is used. Furthermore, two aggregation operators, namely the $ 2 $-tuple linguistic $ q $-rung picture fuzzy Einstein weighted average and the $ 2 $-tuple linguistic $ q $-rung picture fuzzy Einstein order weighted average, are introduced. Our inspiration for employing the notion of $ 2 $TL$ q $-RPFSs is the ability of $ q $-RPFSs to support a wide range of information and the significant qualities of $ 2 $-tuple linguistic term sets to handle qualitative data. Congested transportation networks may be made more efficient by leveraging digital transformation. Real-time traffic management is one solution to the problem of road congestion. As a result of connected autonomous vehicle (CAV) advances, the benefits of real-time traffic management systems have grown dramatically. CAVs can help manage traffic by acting as enforcers. To complement the extended approach, the proposed technique is used to select the best alternative for a real-time traffic management system. The performance of the suggested technique is validated using scenario analysis. The results show that the suggested strategy is efficient and relevant to real-world situations.

Many real-world decision-making issues frequently involve competing sets of criteria, uncertainty, and inaccurate information. Some of these require the involvement of a group of decision-makers, where it is necessary to reduce the various available individual preferences to a single collective preference. To enhance the effectiveness of multi-criteria decisions, multi-criteria decision-making is a popular decision-making technique that makes the procedure more precise, reasonable, and efficient. The "Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)" and "Elimination and Choice Transforming Reality (ELECTRE)" are prominent ranking methods and widely used in the multi-criteria decision-making to solve complicated decision-making problems. In this study, two $ m $-polar fuzzy set-based ranking methods are proposed by extending the ELECTRE-Ⅰ and TOPSIS approaches equipped with cubic $ m $-polar fuzzy (C$ m $PF) sets, where the experts provide assessment results on feasible alternatives through a C$ m $PF decision matrix. The first proposed method, C$ m $PF-TOPSIS, focuses on the alternative that is closest to a C$ m $PF positive ideal solution and farthest away from the C$ m $PF negative ideal solution. The Euclidean and normalized Euclidean distances are used to determine the proximity of an alternative to ideal solutions. In contrast, the second developed method is C$ m $PF-ELECTRE-Ⅰ which uses an outranking directed decision graph to determine the optimal alternative, which entirely depends on the C$ m $PF concordance and discordance sets. Furthermore, a practical case study is carried out in the diagnosis of impulse control disorders to illustrate the feasibility and applicability of the proposed methods. Finally, a comparative analysis is performed to demonstrate the veracity, superiority, and effectiveness of the proposed methods.

Aggregation is a very efficient indispensable tool in which several input values are transformed into a single output value that further supports dealing with different decision-making situations. Additionally, note that the theory of m-polar fuzzy (mF) sets is proposed to tackle multipolar information in decision-making problems. To date, several aggregation tools have been widely investigated to tackle multiple criteria decision-making (MCDM) problems in an m-polar fuzzy environment, including m-polar fuzzy Dombi and Hamacher aggregation operators (AOs). However, the aggregation tool to deal with m-polar information under Yager's operations (that is, Yager's t-norm and t-conorm) is missing in the literature. Due to these reasons, this study is devoted to investigating some novel averaging and geometric AOs in an mF information environment through the use of Yager's operations. Our proposed AOs are named as the mF Yager weighted averaging (mFYWA) operator, mF Yager ordered weighted averaging operator, mF Yager hybrid averaging operator, mF Yager weighted geometric (mFYWG) operator, mF Yager ordered weighted geometric operator and mF Yager hybrid geometric operator. The initiated averaging and geometric AOs are explained via illustrative examples and some of their basic properties, including boundedness, monotonicity, idempotency and commutativity are also studied. Further, to deal with different MCDM situations containing mF information, an innovative algorithm for MCDM is established under the under the condition of mFYWA and mFYWG operators. After that, a real-life application (that is, selecting a suitable site for an oil refinery) is explored under the conditions of developed AOs. Moreover, the initiated mF Yager AOs are compared with existing mF Hamacher and Dombi AOs through a numerical example. Finally, the effectiveness and reliability of the presented AOs are checked with the help of some existing validity tests.

ABSTRACT Brachybacterium species have been identified in various ecological niches and belong to the family Dermabacteriaceae within the phylum Actinobacteria. In this study, we isolated a novel Brachybacterium equifaecis JHP9 strain from horse feces and compared its kinetic, biochemical, and genomic features with those of other Brachybacterium strains. Moreover, comparative genomic analysis using publicly available Brachybacterium genomes was performed to determine the properties involved in their ecological adaptation and metabolic potential. Novel species delineation was determined phylogenetically through 16S rRNA gene similarity (up to 97.9%), average nucleotide identity (79.5–82.5%), average amino acid identity (66.7–75.8%), and in silico DNA-DNA hybridization (23.7–27.9) using closely related strains. This study also presents the first report of the kinetic properties of Brachybacterium species. Most of the Brachybacterium strains displayed high oxygen (K m(app) =1.6–24.2 µM) and glucose (K m(app) =0.73–1.22 µM) affinities, which may manifest niche adaptations. Various carbohydrate metabolisms under aerobic and anaerobic conditions, antibiotic resistance, mobile genetic elements, carbohydrate-active enzymes, lactic acid production, and the clustered regularly interspaced short palindromic repeats-Cas and bacteriophage exclusion systems were observed in the genotypic and/or phenotypic properties of Brachybacterium species, suggesting their genome flexibility, defense mechanisms, and adaptability. Our study contributes to the knowledge of the kinetic, physiological, and genomic properties of Brachybacterium species, including the novel JHP9 strain, which advocates for their tolerant and thriving nature in various environments, leading to their ecological adaptation. IMPORTANCE Basic physiological and genomic properties of most of the Brachybacterium isolates have been studied; however, the ability of this bacterium to adapt to diverse environments, which may demonstrate its role in niche differentiation, is to be identified yet. Therefore, here, we explored cellular kinetics, metabolic diversity, and ecological adaptation/defensive properties of the novel Brachybacterium strain through physiological and comparative genomic analysis. In addition, we presented the first report examining Brachybacterium kinetics, indicating that all strains of Brachybacterium, including the novel one, have high oxygen and glucose affinity. Furthermore, the comparative genomic analysis also revealed that the novel bacterium contains versatile genomic properties, which provide the novel bacterium with significant competitive advantages. Thus, in-depth genotypic and phenotypic analysis with kinetic properties at the species level of this genus is beneficial in clarifying its differential characteristics, conferring the ability to inhabit diverse ecological niches.

This paper develops the ELiminating Et Choice Translating REality (ELECTRE) method under the generalized environment of complex spherical fuzzy $ N $-soft sets ($ CSFN\mathcal{S}_{f}Ss $) that have distinctive and empirical edge of non-binary parametrization and also indeed overcome the limitations and flaws of existing ELECTRE I methods. We propose an innovatory decision-making technique, namely, $ CSFN\mathcal{S}_{f} $-ELECTRE I method where the data and information are in modern modes. The proposed $ CSFN\mathcal{S}_{f} $-ELECTRE I method enjoys all the distinct and modern attributes of uncertain information which mainly comprises of parameterizations, neutral perspective, multi-valuation and two-dimensional representations. We support the proposed work by a flowchart along with an algorithm and then utilize it to solve the MAGDM problem under $ CSFN\mathcal{S}_{f} $ environment. This novel technique employs the principles of $ CSFN\mathcal{S}_{f} $ concordance and $ CSFN\mathcal{S}_{f} $ discordance sets which are established on score and accuracy functions and engrossed to enjoin the most superior alternative. Ultimately, the decision graph and aggregated outranking Boolean matrix are formulated by merging the outcomes of $ CSFN\mathcal{S}_{f} $ concordance and $ CSFN\mathcal{S}_{f} $ discordance indices which are evaluated through score function and distance measures, respectively. Moreover, linear-ranking order is evaluated which provides linear ordering of decision alternatives. A prime MAGDM problem of poverty alleviation is addressed from socio-economic field that approve the flexibility of the intended approach. We perform a sustaining comparison with another approach (CSF-ELECTRE I approach) to assure the productivity and potency of the proposed methodology. We also provide an allegorical line graph of this comparison that demonstrate the admissibility of the resulting outcomes.

The occurrence and spread of antibiotic resistance have become a pressing global health concern. Understanding the genetic elements that facilitate the dissemination of antibiotic resistance genes (ARGs) in marine environments is crucial for effective microbial surveillance and management strategies. This study aimed to reveal the presence of mobilizable multiresistance clusters, consisting of ARGs associated with mobile genetic elements (MGEs), in marine bacterial communities. Water samples were collected from two beaches in Jeju, South Korea, and screened to identify multi-drug resistant bacteria. A total of 20 bacterial isolates were selected for whole genome sequencing, and through comprehensive genomic analysis, we identified and characterized nine such clusters primarily composed of betalactams, aminoglycosides, and tetracycline ARGs associated with MGEs like IS6, IS9, and Tn3. Additionally, an extensive analysis of 900 marine bacterial genomes from the National Center for Biotechnology Information (NCBI) database was conducted to gain a broader perspective. Our results provide valuable insights into the prevalence and diversity of mobilizable multiresistance clusters in marine bacterial communities.

Interactions between metals and microbes are critical in geomicrobiology and vital in microbial ecophysiological processes. Methane-oxidizing bacteria (MOB) and ammonia-oxidizing microorganisms (AOM) are key members in aerobic environments to start the C and N cycles. Ammonia and methane are firstly oxidized by copper-binding metalloproteins, monooxygenases, and diverse iron and copper-containing enzymes that contribute to electron transportation in the energy gain pathway, which is evolutionally connected between MOB and AOM. In this review, we summarized recently updated insight into the diverse physiological pathway of aerobic ammonia and methane oxidation of different MOB and AOM groups and compared the metabolic diversity mediated by different metalloenzymes. The elevation of iron and copper concentrations in ecosystems would be critical in the activity and growth of MOB and AOM, the outcome of which can eventually influence the global C and N cycles. Therefore, we also described the impact of various concentrations of metal compounds on the physiology of MOB and AOM. This review study could give a fundamental strategy to control MOB and AOM in diverse ecosystems because they are significantly related to climate change, eutrophication, and the remediation of contaminated sites for detoxifying pollutants.

Topological indices correlate certain physicochemical properties like boiling point, stability, and strain energy of chemical compounds. In this report, we compute M-polynomials for PAMAM dendrimers and polyomino chains. Moreover, by applying calculus, we compute nine important topological indices of under-study dendrimers and chains.

In this paper, a consensus-based method for multi-person decision making (MPDM) using product transitivity with incomplete fuzzy preference relations (IFPRs) is proposed. Additionally, an average aggregation operator has been used at the first level to estimate the missing preference values and construct the complete fuzzy preference relation (FPR). Then it is confirmed to be product consistent by using the transitive closure formula. Following this, weights of decision makers (DMs) are evaluated by merging consistency weights and predefined priority weights (if any). The consistency weights for the DMs are estimated through product consistency investigation of the information provided by each DM. The consensus process determines whether the selection procedure should be initiated or not. The hybrid comprises of a quitting process and feedback mechanism, and is used to enhance the consensus level amongst DMs in case of an inadequate state. The quitting process arises when some DMs decided to leave the course, and is common in MPDM while dealing with a large number of alternatives. The feedback mechanism is the main novelty of the proposed technique which helps the DMs to improve their given preferences based on this consistency. At the end, a numerical example is deliberated to measure the efficiency and applicability of the proposed method after the comparison with some existing models under the same assumptions. The results show that proposed method can offer useful comprehension into the MPDM process.

The q-rung orthopair fuzzy set is a powerful tool for depicting fuzziness and uncertainty, as compared to the Pythagorean fuzzy model. The aim of this paper is to present q-rung orthopair fuzzy competition graphs (q-ROFCGs) and their generalizations, including q-rung orthopair fuzzy k-competition graphs, p-competition q-rung orthopair fuzzy graphs and m-step q-rung orthopair fuzzy competition graphs with several important properties. The study proposes the novel concepts of q-rung orthopair fuzzy cliques and triangulated q-rung orthopair fuzzy graphs with real-life characterizations. In particular, the present work evolves the notion of competition number and m-step competition number of q-rung picture fuzzy graphs with algorithms and explores their bounds in connection with the size of the smallest q-rung orthopair fuzzy edge clique cover. In addition, an application is illustrated in the soil ecosystem with an algorithm to highlight the contributions of this research article in practical applications.

Graph theory plays a substantial role in structuring and designing many problems. A number of structural designs with crossings can be found in real world scenarios. To model the vagueness and uncertainty in graphical network problems, many extensions of graph theoretical ideas are introduced. To deal with such uncertain situations, the present paper proposes the concept of Pythagorean fuzzy multigraphs and Pythagorean fuzzy planar graphs with some of their eminent characteristics by investigating Pythagorean fuzzy planarity value with strong, weak and considerable edges. A close association is developed between Pythagorean fuzzy planar and dual graphs. This paper also includes a brief discussion on non-planar Pythagorean fuzzy graphs and explores the concepts of isomorphism, weak isomorphism and co-weak isomorphism for Pythagorean fuzzy planar graphs. Moreover, it presents a problem that shows applicability of the proposed concept.

Topological indices are numerical parameters used to study the physical and chemical properties of compounds. In quantitative structure–activity relationship QSARs, topological indices correlate the biological activity of compounds with their physical properties like boiling point, stability, melting point, distortion, and strain energy etc. In this paper, we determined the M-polynomials of the crystallographic structure of the molecules Cu2O and TiF2 [p,q,r]. Then we derived closed formulas for some well-known topological indices using calculus. In the end, we used Maple 15 to plot surfaces associated with the topological indices of Cu2O and TiF2 [p,q,r].

Topological indices collect information from the graph of molecule and help to predict properties of the underlying molecule. Zagreb indices are among the most studied topological indices due to their applications in chemistry. In this paper, we compute first and second reverse Zagreb indices, reverse hyper-Zagreb indices and their polynomials of Prophyrin, Propyl ether imine, Zinc Porphyrin and Poly (ethylene amido amine) dendrimers.

Many degree-based topological indices can be obtained from the closed-off M-polynomial of a carbon nanocone. These topological indices are numerical parameters that are associated with a structure and, in combination, determine the properties of the carbon nanocone. In this paper, we compute the closed form of the M-polynomial of generalized carbon nanocone and recover many important degree-based topological indices. We use software Maple 2015 (Maplesoft, Waterloo, ON, Canada) to plot the surfaces and graphs associated with these nanocones, and relate the topological indices to the structure of these nanocones.

This paper investigates the influences of biomass energy, fossil fuel, and some controlled variables on CO2 emission in African countries over the 1980–2014 period. The study employs pool mean group (PMG), mean group (MG), and dynamic fixed effect (DFE) estimators. In addition, it employs weighted fully modified ordinary least squares and weighted dynamic ordinary least squares to validate the robustness of estimates. The results reveal that the relation of fossil fuel with CO2 is positively significant. Conversely, biomass energy exerts a significant negative impact on CO2. In addition, the dampening effect of biomass energy utilization on CO2 emission helps to validate the Environmental Kuznets Curve hypothesis. [ABSTRACT FROM AUTHOR]