Chemical Effects Research Articles

Nutrient Chemical Forms, Storage Effects and Phyto-Toxicity of Organic Fertilizers to Selected Cereal and Legume Crops

The study aims to determine the nutrient chemical forms, storage effects, and phytotoxicity of fertilizers made from nutrient-rich materials and municipal organic waste in order to control the impact of farming practices on the ecology. Laboratory-scale experiments were conducted at 3-month intervals over a period of 15 months to determine the binding forms of phosphate and nitrogen, and other quality parameters of fertilizers. The germination index (GI) method was used to assess the phytotoxicity of the fertilizers at three different rates of applications- 2.0, 2.5, and 3.0 tonnes ha−1 on maize (Zea mays L.) and soybean (Glycine max). It was found that animal-based and organic mixture fertilizers had the highest levels of ammoniacal nitrogen and nitrate: NH4 +-N (0.3 ± 0.0%) and NO3-N (0.7 ± 0.0%), respectively. Rock-based fertilizer had the highest levels of water-soluble (7.0 ± 0.0%) and neutral ammonium citrate soluble (4.1 ± 0.0%) forms of nitrogen and potassium, which are readily available to crops. The GI values of the fertilizers were generally above the safety standard of ≥80, except for synthetic fertilizer when applied on soybeans at 3.0 tonnes ha−1 (74.2). While organic fertilizers were deemed safe for application on the test crops, it is advised to avoid storing the fertilizers for an extended period of time due to potential chemical and biological changes that might affect the biome.

Network for forest by-products charcoal, resin, tar, potash (COST Action EU-PoTaRCh)

COST Action EU-PoTaRCh establishes a network focused on the past, present and future use of the major forest by-products in Europe. The Action emphasizes forest by-products, mainly potash, tar, resin, and charcoal (PoTaRCh), as representatives of the traditional heritage of forest exploitation, including extractives used along the time for their specific chemical, biological activity and therapeutic effect. The scientific objective of the Action is to demonstrate the value of these products for the communities and their socio-economic growth, as well as their impact on biodiversity and climate throughout time. The general aim is to identify and assess changes in production and use of PoTaRCh and extractives, along with their social and environmental impacts on sustainable development, and draw lessons for the future based on this legacy. In this way, the Action supports the sustainable use of forests and the transfer of knowledge about circular economy practices, as a contribution to the systemic shift to the new circular bio-economy. A key component of the Action is to support stakeholders that are knowledgeable about PoTaRCh goods and are interested in them because they are used in production, education and promotion of our natural and cultural heritage. The Action meets a wide range of demands thanks to the participation of partners with various activity profiles (museums, state forests, forest industry, tradition bearers associations, tourism industry, etc.). The EU-PoTaRCh Action highlights three COST inclusivity policies: the participation of inclusivity Target Countries with a long history of developing PoTaRCh, a special emphasis on gender balance, and the involvement of young researchers in leadership positions.

Exploring Excited State Landscapes with Surface Enhanced Hyper-Raman Spectroscopy.

In this Perspective, we provide a historical overview of the surface-enhanced hyper-Raman scattering (SEHRS) effect, describe its essential components, highlight the close connection between theory and experiment in several vignettes, and discuss recent analytical applications. SEHRS, the two-photon analog of surface-enhanced Raman scattering (SERS), is a spontaneous nonlinear scattering exhibited by molecules in a plasmonic field. Hyper Raman provides distinctive information on the molecular vibrations and electronic excited states of analytes. A 40-year old mystery surrounding the SEHRS spectra of R6G is used to illustrate the power of SEHRS to explore excited electronic states, revealing how non-Condon effects can influence the two-photon molecular properties. The exceptionally large enhancement factors (>1013) obtained from SEHRS enable the analysis of single molecules and molecules at very low concentrations. This high sensitivity is further augmented by an increased sensitivity to chemical effects, allowing SEHRS to probe changes in the local environment and the orientation of surface ligands. As most SEHRS experiments employ near-infrared (NIR) and short-wave infrared (SWIR) light, it also holds promise for bioimaging studies. Before concluding, we discuss future directions and challenges for the field as it moves forward.

A brief review on models for birds exposed to chemicals.

"A Who's Who of pesticides is therefore of concern to us all. If we are going to live so intimately with these chemicals eating and drinking them, taking them into the very marrow of our bones - we had better know something about their nature and their power."-Rachel Carson, Silent Spring. In her day, Rachel Carson was right: plant protection products (PPP), like all the other chemical substances that humans increasingly release into the environment without further precaution, are among our worst enemies today (Bruhl and Zaller, 2019; Naidu etal., 2021; Tang etal., 2021; Topping etal., 2020). All compartments of the biosphere, air, soil and water, are potential reservoirs within which all species that live there are impaired. Birds are particularly concerned: PPP are recognized as a factor in the decline of their abundance and diversity predominantly in agricultural landscapes. Due to the restrictions on vertebrates testing, in silico-based approaches are an ideal choice alternative given input data are available. This is where the problem lies as we will illustrate in this paper. We performed an extensive literature search covering a long period of time, a wide diversity of bird species, a large range of chemical substances, and as many model types as possible to encompass all our future need to improve environmental risk assessment of chemicals for birds. In the end, we show that poultry species exposed to pesticides are the most studied at the individual level with physiologically based toxicokinetic models. To go beyond, with more species, more chemical types, over several levels of biological organization, we show that observed data are crucially missing (Gilbert, 2011). As a consequence, improving existing models or developing new ones could be like climbing Everest if no additional data can be gathered, especially on chemical effects and toxicodynamic aspects.

Sex-Specific Associations between Prenatal Exposure to Bisphenols and Phthalates and Infant Epigenetic Age Acceleration.

We examined whether prenatal exposure to two classes of endocrine-disrupting chemicals (EDCs) was associated with infant epigenetic age acceleration (EAA), a DNA methylation biomarker of aging. Participants included 224 maternal-infant pairs from a Canadian pregnancy cohort study. Two bisphenols and 12 phthalate metabolites were measured in maternal second trimester urines. Buccal epithelial cell cheek swabs were collected from 3 month old infants and DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The Pediatric-Buccal-Epigenetic tool was used to estimate EAA. Sex-stratified robust regressions examined individual chemical associations with EAA, and Bayesian kernel machine regression (BKMR) examined chemical mixture effects. Adjusted robust models showed that in female infants, prenatal exposure to total bisphenol A (BPA) was positively associated with EAA (B = 0.72, 95% CI: 0.21, 1.24), and multiple phthalate metabolites were inversely associated with EAA (Bs from -0.36 to -0.66, 95% CIs from -1.28 to -0.02). BKMR showed that prenatal BPA was the most important chemical in the mixture and was positively associated with EAA in both sexes. No overall chemical mixture effects or male-specific associations were noted. These findings indicate that prenatal EDC exposures are associated with sex-specific deviations in biological aging, which may have lasting implications for child health and development.

Integrated assessment of the chemical, microbiological and ecotoxicological effects of a bio-packaging end-of-life in compost

The present study aimed to i) assess the disintegration of a novel bio-packaging during aerobic composting (2 and 6 % tested concentrations) and evaluate the resulting compost ii) analyse the ecotoxicity of bioplastics residues on earthworms; iii) study the microbial communities during composting and in ‘earthworms’ gut after their exposure to bioplastic residues; iv) correlate gut microbiota with ecotoxicity analyses; v) evaluate the chemico-physical characterisation of bio-packaging after composting and earthworms' exposure.Both tested concentrations showed disintegration of bio-packaging close to 90 % from the first sampling time, and compost chemical analyses identified its maturity and stability at the end of the process.Ecotoxicological assessments were then conducted on Eisenia fetida regarding fertility, growth, genotoxic damage, and impacts on the gut microbiome. The bioplastic residues did not influence the earthworms' fertility, but DNA damages were measured at the highest bioplastic dose tested. Furthermore bioplastic residues did not significantly affect the bacterial community during composting, but compost treated with 2 % bio-packaging exhibited greater variability in the fungal communities, including Mortierella, Mucor, and Alternaria genera, which can use bioplastics as a carbon source. Moreover, bioplastic residues influenced gut bacterial communities, with Paenibacillus, Bacillus, Rhizobium, Legionella, and Saccharimonadales genera being particularly abundant at 2 % bioplastic concentration. Higher concentrations affected microbial composition by favouring different genera such as Pseudomonas, Ureibacillus, and Streptococcus.For fungal communities, Pestalotiopsis sp. was found predominantly in earthworms exposed to 2 % bioplastic residues and is potentially linked to its role as a microplastics degrader. After composting, Attenuated Total Reflection analysis on bioplastic residues displayed evidence of ageing with the formation of hydroxyl groups and amidic groups after earthworm exposure.

Synthesis of Nixp/C Nanofibers As Interlayer and Sulfur Host for Lithium-Sulfur Batteries

Lithium-sulfur batteries (LSB) have a high theoretical capacity (1675 mAh g − 1) and energy density (2600 Wh kg−1), making them one of the most promising energy storage systems. 1 However, it has some limitations, such as “shuttle effect” of polysulfides and high volume expansion, causing poor cycle performance of the battery.The transition metal phosphides with carbon materials as sulfur host for LSB have attracted extensive scientific focus due to the large surface area and strong chemisorption ability. Moreover, high electrical conductivity of carbon-based material and the chemical adsorption effect of Ni-P phase can reduce the “shuttle effect”, and improve the cyclability of the material. 2,3 In this work, nickel phosphide carbon composite (NixP/C) nanofibers were synthesized using a water-soluble carbon source polyvinylpyrrolidone (PVP) and cost-effective electrospinning method. The impact of humidity on the physical and electrochemical characteristics of the electrospun NixP/C nanofibers was studied, utilizing them as interlayer and sulfur host material for LSB.The NixP/C nanofibers were synthesized using an electrospinning machine from PVP, nickel nitrate hexahydrate, and phosphoric acid as precursors. The nanofibers were electrospun at 18 kV voltage and 0.8 mL h–1 flow rate. The electrospinning humidity (RH) varied between 19-35%. Obtained nanofibers were dried at 110 ºC for 11 h. Finally, prepared fibers were annealed at 700 ºC for 1 h with a heating rate of 5 ºC min-1 in the N2 + H2 (4%) atmosphere.The crystalline phases of the final products were observed using X-Ray diffraction (XRD, Miniflex, Rigaku). The microstructure was studied by transmission electron microscopy (TEM, JEM-1400 Plus, JEOL). According to the results shown in Figure 1, Ni2P with a hexagonal structure and the space group of P62m, and Ni12P5 with a tetragonal structure, space group of 87:I4/m were formed. Nanoparticles of NixP are uniformly distributed within the carbon fiber matrix (inset).The NixP/C freestanding mats were embedded as a sulfur host or interlayer for LSB in CR2032 coin-type cells. 1 M Li2S6 catholyte solution and 1 M LiTFSI in 1,3- dioxolane (DOL)/1,2 dimethoxyethane (DME) (v/v, 1:1) with 2 wt% of LiNO3 were used as a source of sulfur and electrolyte, respectively. Further details and obtained results will be presented at the conference. Acknowledgements This research was funded by the projects AP13068219 “Development of multifunctional free-standing carbon composite nanofiber mats”, and AP19675260 “Development of nanofibrous electrode materials for next-generation lithium-ion batteries” from the Ministry of Education and Science of the Republic of Kazakhstan.

(Invited) Application of Nanostructure for Improving the Interfacial Interactions between Sensing Surface and Targeted Particles

Various interfacial interactions, encompassing screened Coulomb (electrostatic double layer) forces, Lifshitz-van der Waals forces, hydrophobic/hydrophilic interactions, as well as steric, chemical, morphological, and roughness effects, have been confirmed to play a crucial role in governing the interaction between target particles and the sensing surface. Small protrusions on the sensing surface can induce substantial variations in the surface’s interaction with the target analytes based on the extended Derjauin-Landau-Verwey-Overbeek (DLVO) theory. 1 Here, indium tin oxide coated vertical nanowires served as nanostructure to investigate interfacial interactions between the sensing surface and targeted analytes. Analyzing the ratio of particle size to asperity size on the sensing surface within the extended DLVO theory revealed that surface roughness can provide sufficient interfacial interactions with target analytes, thereby enhancing the electrical sensing performance. Upon immersing the nanostructural sensing surface in an analyte solution, electrical signals undergo a significant shift owing to alterations in the surface potential at the interface between the functionalized sensing surface (such as antibodies or chemical functional groups) and the analyte solution. 2, 3 These observations highlight the critical role of nanostructure on the sensing surface, particularly with adequate surface roughness, in significantly improving sensing performance by facilitating effective interaction of the surface with the target analyte based on the extended DLVO theory.

Novel analytical solution for solvent-solute flow: Application to pressure transmission testing of reactive shales

Coupled solvent-solute flow is a common phenomenon observed while drilling shale formations using water-based fluids, leading to unfavorable outcomes. Designing optimal fluid formulation requires laboratory tests, such as pressure transmission tests, to evaluate shale-fluid interactions. In this study, an analytical solution was derived for the coupled flow of solvent-solute under pressure transmission testing conditions. It was derived based on the semi-infinite domain solution employing the method of images. The solution was then verified against the semi-analytical solution from the literature. The analysis of the solution revealed that early time pressure response at the outer boundary is primarily governed by hydraulic diffusivity while late time response is by ion diffusion. It also showed that the coefficient of lambda, introduced during derivations, quantifies the chemical effects. In addition, sensitivity analysis was conducted to better understand how variations in key parameters impact the overall transport processes within reactive shales. Finally, a good agreement was obtained by comparing the analytical solution with experimental data from various published sources. The solution will help researchers in gaining new insights into the shale fluid interactions and designing optimal fluid formulations.

Current Review: Alginate in the Food Applications

Due to global development and increased public awareness of food’s effects on health, demands for innovative and healthy products have risen. Biodegradable and environmentally friendly polymer usage in modern food products is a promising approach to reduce the negative health and environmental effects of synthetic chemicals. Also, desirable features such as flavor, texture, shelf-life, storage condition, water holding capacity, a decrease in water activity, and an oil absorption of fried food have been improved by many polysaccharides. One of the important polymers, which is applied in the food industry, is alginate. Alginates are a safe and widely used compound in various industries, especially the food industry, which has led to innovative methods for for the improvement of this industry. Currently, different applications of alginate in stable emulsions and nano-capsules in food applications are due to the crosslinking properties of alginate with divalent cations, such as calcium ions, which have been studied recently. The main aim of this review is to take a closer look at alginate properties and applications in the food industry.

Flusilazole induced developmental toxicity, neurotoxicity, and cardiovascular toxicity via apoptosis and oxidative stress in zebrafish

Flusilazole is a well-known triazole fungicide applied to various crops and fruits worldwide. Flusilazole residues are frequently detected in the environment, and many researchers have reported the hazardous effects of flusilazole on non-target organisms; however, the developmental toxicity of flusilazole has not been fully elucidated. In this study, we investigated flusilazole-induced developmental defects in zebrafish, which are used in toxicology studies to assess the toxic effects of chemicals on aquatic species or vertebrates. We confirmed that flusilazole exposure affected the viability and hatching rate of zebrafish larvae, and resulted in morphological defects, reduced body length, diminished eye and head sizes, and inflated pericardial edema. Apoptosis, oxidative stress, and inflammation were also observed. These factors interrupted the normal organ formation during early developmental stages, and transgenic models were used to identify organ defects. We confirmed the effects of flusilazole on the nervous system using olig2:dsRed transgenic zebrafish, and on the cardiovascular system using cmlc2:dsRed and fli1:eGFP transgenic zebrafish. Our results demonstrate the developmental toxicity of flusilazole and its mechanisms in zebrafish as well as the detrimental effects of flusilazole.

Modelling and simulation on compressible multi-component gas-liquid flows with chemical reaction and phase transition effects

In this paper, mathematical models and numerical algorithm are conducted for simulating compressible two-phase multi-component reactive flows, coupling with the finite-rate-based chemistry and the instantaneous-equilibrium phase transition model. Distinctive from previous multi-component two-phase governing equations, all volume fraction transport equations, with non-conservative characteristics, of gaseous components are substituted with a thermal equilibrium assumption inside the gaseous mixture for closure. Moreover, based on the temperature polynomial (NASA-7) fitted gas properties and the stiffened gas equation of state (SG-EOS) described liquid properties, the instantaneous-equilibrium phase transition model is re-derived, and the solving strategy of the transient phase transition model is detailly provided using an algebraical approach rather than the iterative process. Having included these elements, the proposed model is validated on three canonical tests, first for pure reactive flows, second for pure two-phase flows, and third for complex compressible multi-component two-phase reactive flows with phase transition effects: hydrogen-oxygen detonation interacting with a water droplet. The cases have well demonstrated the proposed model capability and the expected fluid physics in both the multiphase and reactive flows are reproduced.

Ppb-level H2 gas-sensor based on porous Ni-MOF derived NiO@CuO nanoflowers for superior sensing performance

Nickel oxide (NiO) is an optimal material for precise detection of hydrogen (H2) gas due to its high catalytic activity and low resistivity. However, the solid structure of NiO imposes limitations on the gas response kinetics of H2 gas molecules, resulting in a slower electron–hole transit and reduced gas response value. Herein, a unique NiO@CuO NFs with porous sharp-tip and nanospheres morphology was successfully synthesized by using a metal–organic framework (MOF) as a precursor. The fabricated porous 2 wt% NiO@CuO NFs describes outstanding selectivity towards H2 gas, including a high sensitivity of response value (170–20 ppm at 150 °C), is almost 28.3 % higher than that of porous Ni-MOF, low detection limit (300 ppb) with a notable response (21), short response and recovery times at (300 ppb, 40/63 s and 20 ppm, 100/167 s), exceptional long-term stability and repeatability. The study also explored the impact of relative humidity to evaluate the sensor performance under real-world conditions. The boosted hydrogen dioxide sensing properties may be attributed to synergistic effects of numerous factors including p-p heterojunction at the interface between NiO and CuO nanoflowers, especially a porous sharp-tip MOF structure and rough surface of nanospheres as well as the chemical sensitization effect of NiO. This research offers a viable method for creating unique MOS heterostructures from Ni-MOF and CuO that have unique morphologies and compositions that could be used for H2 gas sensing applications.

Chemical reaction effects on MHD heat and mass convection of rotating fluid past a moving vertical plate in a porous medium with hall current

This study presents the problem of steady heat mass convective Magnetohydrodynamic (MHD) flow of a moving and rotating fluid over a vertical uniformly moving plate through a porous medium in the presence of a first-order chemical reaction and strong magnetic field where the Hall effect is present. The numerical solutions of similarity equations are obtained by Runge-Kutta fourth order method. The graphical results show the effects of different parameters such as chemical reaction, permeability, wall velocity ratio and rotation parameters on the velocity, temperature and concentration profiles and which can also show a clear difference with the literature results.

A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example

Data scarcity is one of the most critical issues impeding the development of prediction models for chemical effects. Multitask learning algorithms leveraging knowledge from relevant tasks showed potential for dealing with tasks with limited data. However, current multitask methods mainly focus on learning from datasets whose task labels are available for most of the training samples. Since datasets were generated for different purposes with distinct chemical spaces, the conventional multitask learning methods may not be suitable. This study presents a novel multitask learning method MTForestNet that can deal with data scarcity problems and learn from tasks with distinct chemical space. The MTForestNet consists of nodes of random forest classifiers organized in the form of a progressive network, where each node represents a random forest model learned from a specific task. To demonstrate the effectiveness of the MTForestNet, 48 zebrafish toxicity datasets were collected and utilized as an example. Among them, two tasks are very different from other tasks with only 1.3% common chemicals shared with other tasks. In an independent test, MTForestNet with a high area under the receiver operating characteristic curve (AUC) value of 0.911 provided superior performance over compared single-task and multitask methods. The overall toxicity derived from the developed models of zebrafish toxicity is well correlated with the experimentally determined overall toxicity. In addition, the outputs from the developed models of zebrafish toxicity can be utilized as features to boost the prediction of developmental toxicity. The developed models are effective for predicting zebrafish toxicity and the proposed MTForestNet is expected to be useful for tasks with distinct chemical space that can be applied in other tasks.Scieific contributionA novel multitask learning algorithm MTForestNet was proposed to address the challenges of developing models using datasets with distinct chemical space that is a common issue of cheminformatics tasks. As an example, zebrafish toxicity prediction models were developed using the proposed MTForestNet which provide superior performance over conventional single-task and multitask learning methods. In addition, the developed zebrafish toxicity prediction models can reduce animal testing.

The influence of exhaust gas recirculation on combustion and emission characteristics of ammonia-diesel dual-fuel engines: Heat capacity, dilution and chemical effects

As the greenhouse effect intensifies, ammonia is garnering increasing attention as a carbon-free fuel. In the transport sector, ammonia-diesel dual-fuel (ADDF) engines are regarded as an effective means of reducing carbon emissions. The objective of this study is to investigate the combustion and emission optimization of an ADDF engine under high load conditions. To this end, an experimental optimization study of different start of diesel injection timing (SODI) and exhaust gas recirculation (EGR) rates was conducted at a load of 18 bar and an ammonia energy ratio of 80 %. The mechanism of heat capacity, dilution, and chemical effects of EGR was also revealed by numerical simulation based on the separated variables method. It was demonstrated that advancing SODI is effective in enhancing combustion efficiency. However, this approach is limited by the upper limit of in-cylinder pressure and results in higher nitrogen oxides (NOx) emissions, which can be mitigated by the EGR. The heat capacity effect of EGR increases the specific heat capacity and decreases the average temperature. The suppression of the combustion process leads to a reduction in thermal and fuel NOx, but an increase in nitrous oxide (N2O) emissions. The dilution effect of EGR results in insufficient oxygen, which decreases the heat release rate and combustion efficiency. Additionally, the NOx and N2O are significantly reduced. The chemical effect of EGR affects reactive groups and unburned components that accelerate heat release rate and increase accumulated heat release, resulting in significantly higher NOx. The comprehensive effect of EGR results in a decrease in N2O emissions and a significant reduction in thermal and fuel NOx. The EGR and further optimization of SODI enabled the ADDF engine to achieve a gross indicated thermal efficiency of 48.5 % with a load of 18 bar and an ammonia energy ratio of 80 %. In addition, NO emissions were reduced by 32.8 percent and greenhouse gas emissions by 63.3 percent.

Connections between Planetary Populations and Chemical Characteristics of Their Host Stars

Chemical anomalies in planet-hosting stars (PHSs) are studied in order to assess how the planetary nature and multiplicity affect the atmospheric chemical abundances of their host stars. We employ APOGEE DR17 to select thin-disk stars of the Milky Way, and crossmatch them with the Kepler Input Catalog to identify confirmed PHSs, which results in 227 PHSs with available chemical abundance ratios for six refractory elements. We also examine an ensemble of stars without planet signals, which are equivalent to the selected PHSs in terms of evolutionary stage and stellar parameters, to correct for Galactic chemical evolution effects, and derive the abundance gradient of refractory elements over the condensation temperature for the PHSs. Using the Galactic chemical evolution corrected abundances, we find that our PHSs do not show a significant difference in abundance slope from the stars without planets. However, when we examine the trends of the refractory elements of PHSs, based on the total number of their planets and their planet types, we find that the PHSs with giant planets are more depleted in refractory elements than those with rocky planets. Among the PHSs with rocky planets, the refractory depletion trends are potentially correlated with the terrestrial planets’ radii and multiplicity. In the cases of PHSs with giant planets, sub-Jovian PHSs demonstrate more depleted refractory trends than stars hosting Jovian-mass planets, raising questions on different planetary formation processes for Neptune-like and Jupiter-like planets.

Epoxiconazole disturbed metabolic balance and gut microbiota homeostasis in juvenile zebrafish

Epoxiconazole (EPX) is a broad-spectrum fungicide extensively used in agricultural pest control. Emerging evidence suggests that EPX can adversely affect different endpoints in non-target organisms. Here, the toxicity of EPX was assessed using earlier developmental stage of zebrafish as a model to investigate its effects on metabolism and intestinal microbiota after 21 days of exposure. Our findings indicated that EPX exposure resulted in physiological alterations in juvenile zebrafish, including increase in triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), and glycose (Glu). Nile red staining demonstrated enhanced lipid accumulation in juvenile, accompanied by a marked upregulation in the expression of genes associated with TG synthesis. Moreover, EPX led to alterations in amino acids and carnitines levels in 21 dpf (days post fertilization) zebrafish. We also observed that EPX disrupted intestinal barrier function in juvenile zebrafish, manifested by decreasing mucus secretion and changing in genes related to tight junctions. Moreover, for a more comprehensive analysis of the intestinal microbiota in 21 dpf zebrafish, the intestine tissues were dissected under a microscope for 16S rRNA sequencing analysis. The results revealed that EPX altered the structure and abundance of intestinal microflora in zebrafish, including decreased alpha diversity indices and shifted in bacteria at phylum and genus levels. Notably, the correlation analysis demonstrated strong associations between alterations in various pathogenic bacterial genera and levels of amino acids and carnitines. Overall, these findings confirm that the fungicide EPX promotes metabolic disorders and alterations in the intestinal micro-environment in 21 dpf zebrafish, shedding light on the toxicologic effects of chemicals to aquatic organisms during the development stage.

Computation of SWCNT/MWCNT-doped thermo-magnetic nano-blood boundary layer flow with non-Darcy, chemical reaction, viscous heating and Joule dissipation effects

CNTs have been shown to exhibit exceptional electrical and thermal conductivities, chemical and mechanical stability and physiochemical reliability in wide-ranging applications covering biomedicine, energy and aerospace. Motivated by emerging applications in nano-drug delivery in medicine and radiative ablation therapy, a steady-state mathematical model is established for magnetohydrodynamic boundary-layer transport of chemically reactive carbon nanotubes (CNTs)-doped electrically conducting blood along a porous stretching wall of a blood vessel. Multiple and single walls CNTs are considered using the model developed by Xue (2005). Heat generation, radiative flux, wall mass (concentration) slip, viscous heating and Joule magnetic dissipation are incorporated. Chemical reaction effects are addressed utilizing homogenous first-order model. The Darcy-Forchheimer drag force model is utilized for bulk matrix and inertial drag effects in the porous medium. Radiative heat-transport is studied considering Rosseland's diffusion model. The governing partial differential conservation equations for mass, momentum, energy and species are formulated in a two-dimensional Cartesian coordinate system with allied wall and free-stream boundary conditions. Via scaling transformations, a nonlinear boundary value problem is derived. Numerical computations are achieved through bvp4c scheme. The impact of selected parameters on dimensionless quantities (velocity, temperature, concentration, skin friction, local Nusselt and Sherwood numbers) are computed and elaborated through tables and graphs. A good correlation of the numerical solutions with earlier simpler models from the literature is included. The simulations show that with augmentation in Hartmann magnetic number and Forchheimer inertial drag number, significant damping in the nano-doped blood flow is produced for both SWCNTs and MWCNTs. Temperature is elevated with increment in dissipation effect i. e. Eckert number. Higher values of mass (solutal) slip parameter induce a depletion in the concentration. Nusselt number i. e. heat transfer rate to the blood vessel wall is improved with greater values of solid volume fraction for both CNTs. The present model is relevant to radiative ablation therapy combined with nano-medical treatments in blood vessels wherein constant mechanical loading via blood pressure and flow can elevate internal stresses (circumferential wall stress and endothelial shear stress) and induce morphological alterations in blood vessel wall (stretching) and endothelium in conjunction with biochemical reactions.

Development of modified fuzzy FMEA method in environmental risk assessment of earth dams

The investigations have shown that the construction of the dam and its related facilities have significant physical–chemical and ecological effects on the ecosystem. Failure Mode and Effects Analysis (FMEA) is a technique for ranking risks in projects to construct dams, but it has many deficiencies and ambiguities. Therefore, to prevent the shortcomings of the classical method, the modified fuzzy inference system (MFIS-FMEA) method has been used by creating a two-stage model to more accurately assess the risk of Eyvashan Dam. First, all the considered indicators are weighted using the Shannon entropy method, and the environmental risk is prioritized using the Fuzzy OWA method. In this study, two-stage fuzzy reasoning and a Max–Min combination rule are used. When severity (SEV) and occurrence (OCC) variables are combined, the critical risk index (RCI) values are predicted in the first stage. RCI and detection index (DET) input are then used to predict the MFIS-RPN in the second stage. The results of the risk priority number (RPN) in the MFIS-RPN method are much more accurate and serious than the FIS-RPN method due to the two-stage nature and the use of new language terms. The results of the proposed MFIS-RPN technique show that the highest RPN was obtained with immediate action in the dam construction phase for soil erosion and soil pollution and in the dam operation phase for aquatic and water pollution. Therefore, due to the increase in risk score, it is necessary to take immediate and more accurate monitoring during the construction and operation phases.