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The use of antibiotics in poultry feed as a growth promoter has been restricted in many countries around the world. Consequently, there is a growing interest in finding viable alternatives for growth enhancement and disease prevention in the poultry sector. Probiotics are considered alternative feed additives to antibiotics and can be defined as microbial food supplements which beneficially affect the host by improving its intestinal microbial balance. In this review, the special characteristics of probiotics and their mechanisms of action have been described. Probiotics enhance the growth and production of poultry birds, protect the host against pathogens, enhance the immune system, improve bone strength and fight parasitism. In the following paragraphs the available literature on the uses of probiotics in poultry production is reviewed.

The present research is a comparative study that reports an economical and accessible method to synthesize niobium (Nb) and Tantalum (Ta) selenides and tellurides with useful application in the removal of pollutants in textile, paper, and dyeing industries as well as in medical field. In this study, solid-state process was used to generate nanocomposites and various characterization techniques were employed to compare two groups of materials under investigation. Structure, morphology, elemental constitution, and functional groups of synthesized materials were analyzed with XRD, FESEM coupled with EDS, FTIR, and Raman spectroscopy, respectively. HR-TEM images displayed nanoscale particles with tetragonal and monoclinic crystal structures. The optical properties were evaluated in terms of cut-off wavelength and optical band gap using UV-visible spectroscopy. A comparative behavior of both groups of compounds was assessed with regards to their catalytic and microcidal properties. Extracted nanocomposites when used as catalysts, though isomorphs of each other, showed markedly different behavior in catalytic degradation of MB dye in the presence of NaBH4 that was employed as a reducing agent. This peculiar deviation might be attributed to slight structural differences between them. Escherichia coli and Staphylococcus aureus (G –ve and + ve bacteria, respectively) were designated as model strains for in vitro antibacterial tests of both clusters by employing disk diffusion method. Superior antibacterial efficacy was observed for telluride system (significant inhibition zones of 26-35 mm) compared with selenide system (diameter of inhibition zone ranged from 0.8 mm to 1.9 mm). In addition, molecular docking study was undertaken to ascertain the binding interaction pattern between NPs and active sites in targeted cell protein. The findings were in agreement with antimicrobial test results suggesting NbTe4 to be the best inhibitor against FabH and FabI enzymes.

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic data set with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation – including meteorologic forcings, soil, land class, vegetation, and elevation – were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous US at refined 1/24° (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter data set was prepared for the macro-scale variable infiltration capacity (VIC) hydrologic model. The VIC simulation was driven by Daymet daily meteorological forcing and was calibrated against US Geological Survey (USGS) WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter data set may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous US. We anticipate that through this hydrologic parameter data set, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter data set will be provided to interested parties to support further hydro-climate impact assessment.

High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman's rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R>0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.

Assessing uncertainty in decision-making is a major challenge for DecisionMakers (DMs), and the ç-Rung Orthopair Fuzzy Set (g-ROFS) as the direct extension of Intuitionistic Fuzzy Set (IFS) and Pythagorean Fuzzy Set (PFS) play a crucial role in this aspect. The Complex ç-Run Orthopair Fuzzy Set (Cq-ROFS) is a strong tool to deal with imprecision, vagueness, and fuzziness by expanding the scope of Membership Degree (MD) and Non-Membership Degree (NMD) of g-ROFS from real to complex unit disc. In this paper, we develop some new Cq-ROF Hamacher Aggregation Operators (AOs), i.e., the Cq-ROF Hamacher Weighted Averaging (Cq-ROFHWA) operator, the CqROFH Weighted Geometric (Cq-ROFHWG) operator, the Cq-ROFH Ordered Weighted Averaging (Cq-ROFHOWA) operator, and the Cq-ROFH Ordered Weighted Geometric (Cq-ROFHOWG) operator. Subsequently, we establish a novel Cq-ROF graph framework based on the Hamacher operator called Cq-ROFH Graphs (Cq-ROFHGs) and evaluate its energy and Randié energy. In particular, we compute the energy of a splitting Cq-ROFHG and shadow Cq-ROFHG. Further, we describe the notions of Cq-ROFH digraphs (CqROFHDGs). Moreover, an algorithm is given to solve Multiple Attribute Group Making (MAGDM) problems and the main steps are discussed clearly. Finally, a numerical instance related to the Facade Clothing Systems (FCS) selection is presented to show the effectiveness of the developed concepts in decision-making circumstances. In order to verify the effectiveness of our proposed scheme, a comparative analysis with previous approaches is provided.

There is an urgent need for innovative strategies to raise the performance of environmentally stressed plants. The seeds of single-cross yellow Zea mays (L.) hybrid Giza-168 were soaked in Cis-(c-Z-Ck) or trans-zeatin-type cytokinin (t-Z-Ck) solutions at a concentration of 50 or 40 µM, respectively. Salinity stress was imposed at 0, 75 or 150 mM NaCl in the Hoagland nutrient solution (full strength) used for irrigation. The total carotenoids content was negatively affected by only 150 mM NaCl, while both 75 and 150 mM NaCl negatively affected the growth and yield components, relative water content, membrane stability index, photochemical activity, gas exchange, K+ and chlorophyll contents, K+/Na+ ratio, and photosynthetic efficiency. However, all of these traits were significantly improved by c-Z-Ck pretreatment and further enhanced by t-Z-Ck pretreatment compared with the corresponding controls. Furthermore, the contents of proline, soluble sugars, ascorbate, and glutathione, as well as enzymatic antioxidant activities, were significantly elevated by both salt stress concentrations and increased more by both biostimulators compared to the control. Compared to c-Z-Ck, t-Z-Ck was superior in mitigating the harmful effects of the high H2O2 levels caused by salt stress on the levels of malondialdehyde and ion leakage compared to the control. Under normal or stress conditions, t-Z-Ck pretreatment was better than c-Z-Ck pretreatment, while both positively affected maize hormonal contents. As a result, t-Z-Ck is recommended to enhance the growth and productivity of maize plants by suppressing the effects of oxidative stress caused by saline water irrigation.

The main challenge of pan-European groundwater (GW) monitoring is the sparsity of collated water table depth ( wtd ) observations. The wtd anomaly ( wtd a ) is a measure of the increased wtd due to droughts. Combining long short-term memory (LSTM) networks and transfer learning (TL), we propose an AI-based methodology LSTM-TL to produce reliable wtd a estimates at the European scale in the absence of consistent wtd observational data sets. The core idea of LSTM-TL is to transfer the modeled relationship between wtd a and input hydrometeorological forcings to the observation-based estimation, in order to provide reliable wtd a estimates for regions with no or sparse wtd observations. With substantially reduced computational cost compared to physically-based numerical models, LSTM-TL obtained wtd a estimates in good agreement with in-situ wtd a measurements from 2569 European GW monitoring wells, showing r ⩾ 0.5, root-mean-square error ⩽1.0 and Kling-Gupta efficiency ⩾0.3 at about or more than half of the pixels. Based on the reconstructed long-term European monthly wtd a data from the early 1980s to the near present, we provide the first estimate of seasonal wtd a trends in different European regions, that is, significant drying trends in central and eastern Europe, which facilitates the understanding of historical GW dynamics in Europe. The success of LSTM-TL in estimating wtd a also highlights the advantage of combining AI techniques with knowledge contained in physically-based numerical models in hydrological studies.

Water-use efficiency is the amount of carbon assimilated per water used by an ecosystem and a key indicator of ecosystem functioning, but its variability in response to climate change and droughts is not thoroughly understood. Here, we investigated trends, drought response and drivers of three water-use efficiency indices from 1995–2018 in Europe with remote sensing data that considered long-term environmental effects. We show that inherent water-use efficiency decreased by −4.2% in Central Europe, exhibiting threatened ecosystem functioning. In European grasslands it increased by +24.2%, by regulated transpiration and increased carbon assimilation. Further, we highlight modulation of water-use efficiency drought response by hydro-climate and the importance of adaptive canopy conductance on ecosystem function. Our results imply that decoupling carbon assimilation from canopy conductance and efficient water management strategies could make the difference between threatened and well-coping ecosystems with ongoing climate change, and provide important insights for land surface model development.

We describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the upper Bow River basin, a tributary of the South Saskatchewan River, Alberta, Canada. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically based distributed hydrologic models to represent glacier dynamics. We compare predicted variations in glacier extent, snow water equivalent (SWE), and streamflow discharge with satellite estimates of glacier area and terminus position, observed glacier mass balance, observed streamflow and snow water-equivalent measurements, respectively over the period of 1980–2007. Observations of multiple hydroclimatic variables compare well with those simulated with the coupled hydrology-glacier model. Our results suggest that, on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is approximately 22% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 47% in August, whereas for cold years, it can be as small as 15% and the timing of the glacier melt signature can be delayed by a month. The development of this modeling approach sets the stage for future predictions of the influence of warming climate on streamflow in partially glacierized watersheds.

Two reviews are available in published literature relating to the effects of ascorbic acid on poultry performance. The first review was written by Pardue and Thaxton in 1986 who reviewed the role of ascorbic acid in alleviating the negative effect of heat stress in poultry birds. The second review was presented by Whitehead and Keller in 2003, who detailed the general effects of ascorbic acid in poultry birds, not taking into consideration ‘heat stress’. The first review is deficient in the literature published after 1986, while the second review does not describe the effect of ascorbic acid in heat stressed birds. The present review describes the past and present knowledge of ascorbic acid in alleviating heat stress in poultry birds with new aspects. Heat stress is associated with compromised performance and productivity through a decline in feed intake, nutrient utilisation, growth rate, egg production and quality, feed efficiency and immunity. Heat stress is also characterised by a reduced antioxidant status in birds, resulting in increased oxidative stress. Moreover, male fertility is decreased when birds are exposed to heat stress. Supplementation of 250 mg of ascorbic acid per kg of feed has been found to be optimum to improve feed intake, body weight gain, feed efficiency, egg production and quality, nutrient digestibility, immune response and antioxidant status in poultry birds. This work compiles past and present information about the role of ascorbic acid in heat-stressed poultry.