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Microbial communities mediating anaerobic ammonium oxidation (anammox) represent one of the most energy-efficient environmental biotechnologies for nitrogen removal from wastewater. However, little is known about the functional role heterotrophic bacteria play in anammox granules. Here, we use genome-centric metagenomics to recover 17 draft genomes of anammox and heterotrophic bacteria from a laboratory-scale anammox bioreactor. We combine metabolic network reconstruction with metatranscriptomics to examine the gene expression of anammox and heterotrophic bacteria and to identify their potential interactions. We find that Chlorobi-affiliated bacteria may be highly active protein degraders, catabolizing extracellular peptides while recycling nitrate to nitrite. Other heterotrophs may also contribute to scavenging of detritus and peptides produced by anammox bacteria, and potentially use alternative electron donors, such as H 2 , acetate and formate. Our findings improve the understanding of metabolic activities and interactions between anammox and heterotrophic bacteria and offer the first transcriptional insights on ecosystem function in anammox granules. The use of anammox microbiomes to treat wastewater is an escalating biotechnology, yet the functional role heterotrophic bacteria play in these systems remains poorly understood. Here, Lawson et al . use metagenomics and metatranscriptomics to reveal that heterotrophs degrade free peptides, while recycling nitrate to nitrite.

Energy momentum squared gravity (EMSG) (Roshan and Shojai in Phys Rev D 94:044002, 2016) is a cosmological model where the scale factor is non vanishing at all times and hence does not favor big-bang cosmology. However, the profile of density in the radiation-dominated universe shows that EMSG supports inflationary cosmology. Inflationary cosmological models are successful in providing convincing answers to major cosmological issues like horizon problem, flatness problem, and small value of cosmological constant, but hitherto no model of inflation has been observationally confirmed. Owing to this, varying speed of light (VSL) were introduced which are a class of cosmological models which disfavor inflation and propose an alternative route to solve these cosmological issues by just allowing the speed of light (and Newtonian Gravitational constant) to vary. VSL theories were motivated to address the shortcomings of inflation, but do not address the shortcomings related to the initial big-bang singularity. In this spirit, we present here a novel cosmological model which is free from both the “initial big bang singularity” and “inflation” by incorporating a mutually varying speed of light c ( t ) and Newtonian gravitational constant G ( t ) in the framework of EMSG. We report that in EMSG, for a dust universe ( ω = 0 ), cosmological models for a time-varying c ( t ) and G ( t ) and constant c and G are indistinguishable, whereas for a radiation-dominated universe ( ω = 1 / 3 ), a mutually varying c ( t ) and G ( t ) provides an exiting alternative to inflationary cosmology which is also free from the initial big-bang singularity. We further report that for an ansatz of scale factor representing a bouncing cosmological model, the VSL theory can be applied to a quadratic T gravity model to get rid of “inflation” and “big bang singularity” and concurrently solve the above-mentioned cosmological enigmas.

Quantum spin liquids (QSLs) are topological states of matter exhibiting remarkable properties such as the capacity to protect quantum information from decoherence. Whereas their featureless ground states have precluded their straightforward experimental identification, excited states are more revealing and particularly interesting owing to the emergence of fundamentally new excitations such as Majorana fermions. Ideal probes of these excitations are inelastic neutron scattering experiments. These we report here for a ruthenium-based material, α-RuCl 3 , continuing a major search (so far concentrated on iridium materials) for realizations of the celebrated Kitaev honeycomb topological QSL. Our measurements confirm the requisite strong spin–orbit coupling and low-temperature magnetic order matching predictions proximate to the QSL. We find stacking faults, inherent to the highly two-dimensional nature of the material, resolve an outstanding puzzle. Crucially, dynamical response measurements above interlayer energy scales are naturally accounted for in terms of deconfinement physics expected for QSLs. Comparing these with recent dynamical calculations involving gauge flux excitations and Majorana fermions of the pure Kitaev model, we propose the excitation spectrum of α-RuCl 3 as a prime candidate for fractionalized Kitaev physics. Inelastic neutron scattering characterization shows that α-RuCl 3 is close to an experimental realization of a Kitaev quantum spin liquid on a honeycomb lattice. The collective excitations provide evidence for deconfined Majorana fermions.

In recent years, non-magnetic elements-doped oxide materials have been projected as one of the promising materials for application in optoelectronics and spintronics. The primary goal of this research is to look into the influence of Ag on the structural, optical, and dielectric properties of ZnO compounds. The solid-state route method was used to prepare the Ag:ZnO compounds with 0, 3, 6, 9, and 12 at.% of Ag. The analysis of X-ray diffraction (XRD) pattern data reveals that the prepared compounds have been formed as composite-like compounds. The SEM microstructural study reveals the nano-sized grains in the range of 200–300 nm. The elemental color mapping using energy dispersive spectroscopy confirms that no undesirable external impurities were introduced into the final synthesized samples, and all elements are uniformly distributed in the prepared samples. The optical property, investigated through a UV–Vis spectrophotometer, indicates that the band gap has narrowed down upon the increase of Ag content. The transmittance value is found to increase drastically from 5% (for ZnO) to 55% (for 9% Ag:ZnO) compound. The frequency-dependent behavior of dielectric constant, dielectric loss, modulus spectroscopy, and ac conductivity of undoped as well as Ag:ZnO composite-like compounds has been analyzed and well explained with the help of the Maxwell-Weigner model. A further investigation was carried out using impedance spectroscopy to determine the charge transport mechanism that occurs within the grain and grain boundary regions.

Urbanisation is an ever-evolving, complicated continuous process distinct from its surroundings, having the tendency to create a micro-scale system with characteristic local environmental conditions. Large-scale urbanization near the coasts has a definite impact on the coastal processes due to dynamic interactions of the coastal waters with the urban atmospheric, hydrological and anthropogenic residues. This study focuses on understanding the contribution of immediate atmospheric variations due to urbanization on surface temperature of coastal waters along the Mumbai coast. Different meteorological and air quality parameters such as Air Temperature (AT), Land Surface Temperature (LST), Precipitation (P), Relative Humidity (RH), Wind Speed (WS) and Aerosol Optical Depth (AOD) collectively were used as determinants of local urban climatic environment; to analyse and understand the impact of urbanization on Sea Surface Temperature (SST) representing coastal system. ERA5 Reanalysis meteorological data and MODIS satellite data products were used to extract information of the said parameters for a period of 20 years and time-series analysis was performed for each using Mann-Kendall method to establish their trend. Harmonic regression using Autoregressive Integrated Moving Average (ARIMA) and Neural Network Autoregression (NNAR) were used to model the existing and forecast the future trend of SST which showed an increasing trend with comparatively better representation by NNAR (RMSE 0.4 – 0.7 K). Further, a polynomial multiple regression model was built to correlate the influence of all urban climatic parameters with SST, which clearly indicated positive forcing of local climate variation on the coastal waters with an R2 value of 0.93.

Arbuscular mycorrhizal fungi (AMF), glomalin-related soil protein (GRSP), and soil ergosterol are critical bio-indicators of soil health, known for their roles in enhancing nutrient and water absorption by plants. Despite their recognized importance, the interplay among these indicators under the influence of seasonal changes and specific soil amendment practices remains poorly understood, with existing studies showing varied interactions. This study investigates the effects of four distinct soil amendment practices across different seasons on AMF spore density, GRSP levels, and ergosterol content in a Typic Ustochrept soil of North Western India. Results indicate that seasonal dynamics significantly influence these biological features, with soil temperature increases during the summer enhancing all three indicators. Particularly, uncultivated land exhibited the highest levels of AM fungi spore density, GRSP, and ergosterol. In contrast, on cultivated lands, the consistent application of compost mitigated the adverse effects of soil disturbance, maintaining elevated levels of these indicators throughout the year. These findings underscore the potential of targeted soil management practices in maintaining soil health and productivity in variable climatic conditions, emphasizing the role of bio-indicators in sustainable agricultural strategies.

The polycrystalline sample of Ba0.5Sr1.5FeVO6 is prepared by usual mixed oxide technique at optimized temperature of 1125 °C. The X-ray diffraction (XRD) pattern obtained at room temperature confirms the formation of single phase new compound of orthorhombic crystal structure with lattice parameters a = 7.1078 Å, b = 12.6894 Å, and c = 13.8542 Å. The crystallite size of the material is evaluated by Scherre's method and found to be 40 nm. The Scanning electron microscope (SEM) is used to study the surface morphology of the prepared sample which confirms the formation of high-density material. Fourier transformation Infrared (FTIR) Spectroscopy reveals phase identification of the elements associated in the compound due to the presence of low wave number stretching and bending vibrations of respective octahedral VO6, FeO6, and V–O–V. It also identifies the perovskite phase in the wave number range 850–400 cm−1. From dielectric study, room temperature dielectric constant is found to be εr = 250.7, which indicates that the material may be useful for multi-storage device applications. Dielectric characteristics as a function of temperature (25–500 °C) and frequency (100 Hz to 5 MHz) reveal compound that may have multiferroic behavior. For electrical characterization, impedance spectroscopy technique is adopted. It is noticed that material shows non-Debye-type negative temperature coefficient of resistance (NTCR). The conduction behavior of the material basically may be due to defects, oxygen vacancy, and space charge polarization. The current density (J) variation with applied electric field (E) reveals the semiconducting nature. The dc conductivity (σdc) study with inverse of absolute temperature is in accordance with Arrhenius relation.

The National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) is on its way to deploying various operational prediction applications using the Unified Forecast System (https://ufscommunity.org/, last access: 18 June 2022), a community-based coupled, comprehensive Earth modeling system. An aerosol model component developed in collaboration between the Global Systems Laboratory, Chemical Science Laboratory, Air Resources Laboratory, and Environmental Modeling Center (GSL, CSL, ARL, EMC) was coupled online with the FV3 Global Forecast System (FV3GFS) using the National Unified Operational Prediction Capability (NUOPC)-based NOAA Environmental Modeling System (NEMS) software framework. This aerosol prediction system replaced the NEMS GFS Aerosol Component version 2 (NGACv2) system in the National Center for Environment Prediction (NCEP) production suite in September 2020 as one of the ensemble members of the Global Ensemble Forecast System (GEFS), dubbed GEFS-Aerosols v1. The aerosol component of atmospheric composition in the GEFS is based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). GEFS-Aerosols includes bulk modules from the Goddard Chemistry Aerosol Radiation and Transport model (GOCART). Additionally, the biomass burning plume rise module from High-Resolution Rapid Refresh (HRRR)-Smoke based on WRF-Chem was implemented. The GOCART dust scheme was replaced by the FENGSHA dust scheme (developed by ARL). The Blended Global Biomass Burning Emissions Product (GBBEPx version 3) provides biomass burning emission and fire radiative power (FRP) data. The global anthropogenic emission inventories are derived from the Community Emissions Data System (CEDS). All sub-grid-scale transport and deposition are handled inside the atmospheric physics routines, which required consistent implementation of positive definite tracer transport and wet scavenging in the physics parameterizations used by the NCEP's operational FV3GFS. This paper describes the details of GEFS-Aerosols model development and evaluation of real-time and retrospective runs using different observations from in situ measurement and satellite and aircraft data. GEFS-Aerosols predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational NGACv2 system with the fundamental updates (e.g., dust and fire emission) in the atmospheric and chemical transport model.

This paper presents a model that provides the transfer and output characteristic of a grapheme FET transistor. This model also provides close form inquiring expressions for the drain current, trance conductance of the device. In this paper we have investigate the transfer characteristic curve for chemical sensing application. In this present scenario this work proposes to develop a superfast mycotoxin sensor based on Graphene field effect transistor (GFET) using standard microelectronics technology. GFET would be able work in liquid and also in the biological substances. In this work, we will use the simulation program to explore the performance of GFET. The GFET sensor will be integrated to IoT and mobile phone platforms. This study will show that the fully integrated mycotoxin sensor with high sensitivity, fast response, and high dynamic range of toxins concentrations is feasible by proper GFET functionalization.GFET was modelled and simulated Using MATLAB software Introduction.