Some diagnostic analysis of dark energy models with q(z)q(z) parametrizations

The presented paper represents some diagnostic analysis of three dark energy models resulting from the parametrization of the deceleration parameter. All the considered models are interesting as they show intriguing features, such as the late-time acceleration and cosmological phase transition from early deceleration to late acceleration. We use $q(z)$ parametrizations and found the best fitting values of the model parameters by constraining the models with Hubble datasets and Union 2.1 compilation Type Ia supernovae datasets. The evolution of some cosmological parameters is discussed. We aim to discuss the statefinder diagnostic analysis of the considered models and compare it with the $\Lambda$CDM and SCDM models. Moreover, we have performed the Om diagnostics for the models.Comment: 11 pages, 6 figure

A New Cosmological Model: Exploring the Evolution of the Universe and Unveiling Super-Accelerated Expansion

In this paper, we present a cosmological model designed to study the evolution of the universe based on a new parametrization of the deceleration parameter. The model considers a spatially flat, homogeneous, and isotropic Friedmann-Lema\^itre-Robertson-Walker (FLRW) universe filled with radiation, dark matter (DM), and dark energy (DE). We derive the Friedmann equations and the energy conservation equation for the universe, accounting for separate conservation equations for radiation, DM, and DE. Our proposed deceleration parameter is given by a formula involving constants $H_{0}$, $\Omega_{r0}$, $\Omega_{m0}$, $q_{2}$, $q_{1}$, $q_{0}$, $\alpha$ and $\beta$. which we subsequently fit to observational data. To assess the model's viability, we compare it with a diverse range of observational data, including cosmic chronometers, type Ia supernovae, baryon acoustic oscillations, and cosmic microwave background measurements. Employing the chi-square statistic and a Markov Chain Monte Carlo (MCMC) method, we estimate the best-fit values for the free parameters and investigate the constraints imposed by observational data on the model. Our results indicate that our cosmological model provides an excellent fit to the observed data and exhibits a remarkable agreement with the standard $\Lambda$CDM paradigm at higher redshifts. However, the most intriguing discovery lies in the model's prediction of a super-accelerated expansion in the distant future, in contrast to the de Sitter phase predicted by $\Lambda$CDM. This implies the presence of dark energy driving the universe's accelerated expansion. These findings suggest that our proposed cosmological model offers a compelling alternative to the $\Lambda$CDM paradigm, shedding new light on the nature of dark energy and the future fate of the cosmos.Comment: 10 figures, 2 table

Modification of a bi-functional diguanylate cyclase-phosphodiesterase to efficiently produce cyclic diguanylate monophosphate

AbstractCyclic-diGMP is a bacterial messenger that regulates many physiological processes, including many attributed to pathogenicity. Bacteria synthesize cyclic-diGMP from GTP using diguanylate cyclases; its hydrolysis is catalyzed by phosphodiesterases. Here we report the over-expression and purification of a bi-functional diguanylate cyclase-phosphodiesterase from Agrobacterium vitis S4. Using homology modeling and primary structure alignment, we identify several amino acids predicted to participate in the phosphodiesterase reaction. Upon altering selected residues, we obtain variants of the enzyme that efficiently and quantitatively catalyze the synthesis of cyclic-diGMP from GTP without hydrolysis to pGpG. Additionally, we identify a variant that produces cyclic-diGMP while immobilized to NiNTA beads and can catalyze the conversion of [α-32P]-GTP to [32P]-cyclic-diGMP. In short, we characterize a novel cyclic-diGMP processing enzyme and demonstrate its utility for efficient and cost-effective production of cyclic-diGMP, as well as modified cyclic-diGMP molecules, for use as probes in studying the many important biological processes mediated by cyclic-diGMP

Exploring Tidal Force Effects and Shadow Constraints for Schwarzschild-like Black Hole in Starobinsky-Bel-Robinson Gravity

The current manuscript deals with the tidal force effects, geodesic deviation, and shadow constraints of the Schwarzschild-like black hole theorised in Starobinsky-Bel-Robinson gravity exhibiting M-theory compactification. In the current analysis, we explore the radial and angular tidal force effects on a radially in-falling particle by the central black hole, which is located in this spacetime. We also numerically solve the geodesic deviation equation and study the variation of the geodesic separation vector with the radial coordinate for two nearby geodesics using suitable initial conditions. All the obtained results are tested for Sag A* and M87* by constraining the value of the stringy gravity parameter $\beta$ using the shadow data from the event horizon telescope observations. All the results are compared with Schwarzschild black hole spacetime. In our study, we found that both the radial and angular tidal forces experienced by a particle switch their initial behaviour and turn compressive and stretching, respectively, before reaching the event horizon. The geodesic deviation shows an oscillating trend as well for the chosen initial condition. For the constrained value of $\beta$, we see that the spacetime geometry generated by Sag A* and M87* is effectively same for both Schwarzschild and Starobinsky-Bel-Robinson black hole. Furthermore, we also calculated the angular diameter of the shadow in Starobinsky-Bel-Robinson black hole and compared with the Schwarzschild black hole. It is observed that the angular diameter of shadow for M87* and Sgr A* in Starobinsky-Bel-Robinson black hole is smaller than the Schwarzschild black hole. The calculated results satisfy the event horizon telescope observational constraints. Finally, we have concluding remarks.Comment: 12 pages, 18 figures, accepted for publication in European Physical Journal

Effect of gas-to-liquid biosludge on soil properties and alfalfa yields in an arid soil

Soils in Qatar are relatively poor in fertility. Hence, imported top soils and soil enhancing materials are used to improve agricultural yields. Therefore, this work investigated the potential of using gas-to-liquid (GTL) biosludge as a soil conditioner. It sought to increase crop yields in an arid soil with positive environmental footprint in terms of fertilizer application savings, waste utilization and minimization of landfilling. A fodder crop, alfalfa (Medicago sativa), was grown under semi-controlled pot conditions for 12 months. The plant-growth media involved soil, soil + fertilizer, soil + 3% compost, and soil plus five (0.75–12%) biosludge contents. Pertinent properties of the soils, the resulting leachates, and plant growth parameters were analyzed at set periods. Biosludge content generally increased the total porosity and volumetric abundance of different pore types, which in turn affected plant performance, especially the plant height. Alfalfa yield in terms of plant height, aboveground fresh biomass weight and the number of tillers decreased with increasing biosludge content. Mixtures with 0.75–3% biosludge content showed comparable or better plant yield in contrast to the soil, fertilizer and compost controls. The concentration of chemical species in the leachate and plant biomass of biosludge treatments were either lower or similar to the fertilizer and compost controls. Regression modeling identified leachate phosphorus concentrations, soil iron concentration and clay content as the most influential variables for the aforementioned plant performance parameters. The results suggest that GTL biosludge could potentially enhance arid soil properties and improve alfalfa yields

Dataset on the influence of gas-to-liquid biosludge on arid soil properties and growth performance of alfalfa

The dataset presented here is related to our research article entitled “Effect of gas-to-liquid biosludge on soil properties and alfalfa yields in an arid soil” [1]. It relates to selected performance parameters of alfalfa grown in an arid soil amended with five different (0.75–12%) gas-to-liquid biosludge contents, and selected properties of the soil determined using several material characterization techniques. A detailed description of the raw data relating to figures on alfalfa performance parameters such as fresh biomass weight, plant height, the number of tillers, and biomass elemental content in the companion article is provided alongside additional data on the number of days to flowering. The underlying data for leachate from the soil and underlying spectra and diffractograms for the proton nuclear magnetic resonance (1H-NMR) and X-ray diffraction (XRD) data, respectively, shown in the companion article are presented. These show changes in the pore structure characteristics and the mineralogical composition of the soil, soil-fertilizer, soil-biosludge, and soil-compost mixtures tested over time. Additional data showing the effect of the amendments on the bulk and particle densities of the soil is presented. The dataset demonstrates the influence of the industrial biosludge on arid soil properties and alfalfa yields (Kogbara et al., [1])

Dataset comparing the growth of fodder crops and soil structure dynamics in an industrial biosludge amended arid soil

The dataset in this work compares the response of two fodder crops, alfalfa (Medicago sativa) and buffel grass (Cenchrus ciliaris), to industrial biosludge amendment of an arid soil in the State of Qatar. It also evaluates the response of soil structure parameters in the biosludge-amended soils containing the different fodder crops. The dataset relates to our previously published works detailed subsequently. The underlying data comparing the water storage capacity and pore structure evolution of the planted soils treated with 0.75, 1.5, and 3% biosludge contents, which showed good outcomes in the companion articles, alongside soil only and soil-fertilizer controls, are presented. These are shown in terms of the percentage of irrigation water leached, and variations in the logarithmic mean T2 (i.e., T2LM - a proxy for mean pore size) and cumulative porosity, respectively. Data on plant growth parameters such as the number of days to flowering, plant height, and aboveground fresh biomass weight in individual replicates of the different treatments as a percentage of the soil-fertilizer control are also shown. The dataset shows the different responses of both plants and the planted soils to amendments with industrial biosludge from the wastewater treatment plant of a gas-to-liquid (GTL) plant