The morphology of sheep wool applied as organic fertilizer biodegraded in the soil was examined. The investigations were conducted in natural conditions for unwashed waste wool, which was rejected during sorting and then chopped into short segments and wool pellets. Different types of wool were mixed with soil and buried in experimental plots. The wool samples were periodically taken and analyzed for one year using Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray Spectroscopy (EDS). During examinations, the changes in the fibers' morphology were observed. It was stated that cut wool and pellet are mechanically damaged, which significantly accelerates wool biodegradation and quickly destroys the whole fiber structure. On the contrary, for undamaged fibers biodegradation occurs slowly, layer by layer, in a predictable sequence. This finding has practical implications for the use of wool as an organic fertilizer, suggesting that the method of preparation can influence its biodegradation rate. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(SEM)(sic)(sic)(sic)(sic)(sic)X(sic)(sic)(sic)(sic)(EDS)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Lime-activated ground granulated blast furnace slag (GGBS) is usually used to treat gypseous soils. However, sulphate-bearing soils often contain other sulphates, e.g., sodium sulphate (Na2SO4), potassium sulphate (K2SO4) and magnesium sulphate (MgSO4). Therefore, in this study, lime-GGBS was used as a curing agent for stabilising four sulphate-bearing soils, which were named as Na-soil, K-soil, Mg-soil, and Ca-soil. Unconfined compressive strength (UCS), swelling, X-ray diffraction, scanning electron microscopy and inductively coupled plasma spectroscopy tests, were conducted to explore the macro- and micro-properties of the lime-GGBS-stabilised soils. The results showed that at 5000 ppm sulphate, stabilised Mg-soil had the lowest swelling and highest UCS. At 20,000 ppm sulphate, stabilised Ca-soil had the lowest swelling, while stabilised Na-soil had the highest UCS. Generally, increasing sulphate concentration decreased swelling for Ca-soil but increased for other three soils, and decreased UCS for Mg-soil but increased for other three soils. This was because less ettringite was generated in the stabilised Ca-soil and the formation of magnesium silicate hydrate (MSH) in the stabilised Mg-soil. Therefore, the sulphate type had a significant impact on the swelling and strength properties of lime-GGBS-stabilised sulphate-bearing soil. It is essential to identify the sulphate type before stabilising the soil on-site.

An analytical methodology was developed for the first time in this work enabling the simultaneous enantiomeric separation of the fungicide fenpropidin and its acid metabolite by Capillary Electrophoresis. A dual cyclodextrin system consisting of 4 % (w/v) captisol with 10 mM methyl-beta-cyclodextrin was employed in a 100 mM sodium acetate buffer at pH 4.0. Optimal experimental conditions (temperature 25 degrees C, separation voltage -25 kV, and hydrodynamic injection of 50 mbar x 10 s) allowed the simultaneous separation of the four enantiomers in <10.7 min with resolutions of 3.1 (fenpropidin) and 3.2 (its acid metabolite). Analytical characteristics of the method were evaluated and found adequate for the quantification of both chiral compounds with a linearity range from 0.75 to 70 mg L-1, good accuracy (trueness included 100 % recovery, precision with RSD<6 %), and limits of detection and quantification of 0.25 and 0.75 mg L-1, respectively, for the four enantiomers. No significant differences were found between the concentrations determined and labelled of fenpropidin in a commercial agrochemical formulation. The stability over time (0-42 days) of fenpropidin enantiomers using the commercial agrochemical formulation was evaluated in two sugar beet soils, revealing to be stable at any time in one sample, while in the other a decrease of 45 % was observed after 42 days. Individual and combined toxicity of fenpropidin and its metabolite was determined for the first time for marine organism Vibrio fischeri, demonstrating higher damage caused by parent compound. Synergistics and antagonists' interactions were observed at low and high effects levels of contaminants.

Subsequent crops are often sensitive to acetolactate synthase (ALS)-inhibiting herbicide residues, particularly in alkaline soils. The main objective of this study was to compare the impact of different ALS-inhibiting residual herbicides on growth of oil-seed rape (Brassica napus L. subsp. napus) and sugar beet (Beta vulgaris L.) in alkaline soil. In this regard, three experiments were conducted in Prague, Czech Republic, during 2021-2023. In spring, six herbicides (amidosulfuron, chlorsulfuron, imazamox, propoxycarbazone, pyroxsulam, sulfosulfuron) were applied at three application rates (1N - full, 0.5N - half, and 0.05N - 5 % of full). One and four months after application, half of each plot was sown with oilseed rape, and the other half was sown with sugar beet. Herbicide phytotoxicity and aboveground biomass were assessed four weeks after crop emergence. Weather conditions during experimental years, herbicides used, herbicide application rates and the period between herbicide application and crop sowing affected herbicide phytotoxicity and aboveground biomass of both crops. The most damaging effects were recorded with the application of chlorsulfuron for oilseed rape (phytotoxicity was 96-98 % at one month after 1N application) and sulfosulfuron and chlorsulfuron for sugar beet (phytotoxicity was 97-100 % and 90-100 %, respectively). Pyroxsulam caused the least damage to both the crops (average phytotoxicity was 18 %). Herbicide phytotoxicity was 3-times higher, and crop biomass was almost half as much as at the first assessment compared to the second assessment. Sugar beet was more sensitive than oilseed rape to chlorsulfuron and sulfosulfuron, especially in dry conditions, where 0.05 N rates caused biomass reduction of 20-60 % in sugar beet. Most of the tested herbicides could have residual effect that likely damages crops in rotation, particularly if a dry period occurs after the application of herbicides and/or sowing of crops.

Amidst global scarcity, preventing pipeline failures in water distribution systems is crucial for maintaining a clean supply while conserving water resources. Numerous studies have modelled water pipeline deterioration; however, existing literature does not correctly understand the failure time prediction for individual water pipelines. Existing time-to-failure prediction models rely on available data, failing to provide insight into factors affecting a pipeline's remaining age until a break or leak occurs. The study systematically reviews factors influencing time-to-failure, prioritizes them using a magnitude-based fuzzy analytical hierarchy process, and compares results with expert opinion using an in-person Delphi survey. The final pipe-related prioritized failure factors include pipe geometry, material type, operating pressure, pipe age, failure history, pipeline installation, internal pressure, earth and traffic loads. The prioritized environment-related factors include soil properties, water quality, extreme weather events, temperature, and precipitation. Overall, this prioritization can assist practitioners and researchers in selecting features for time-based deterioration modelling. Effective time-to-failure deterioration modelling of water pipelines can create a more sustainable water infrastructure management protocol, enhancing decision-making for repair and rehabilitation. Such a system can significantly reduce non-revenue water and mitigate the socio-environmental impacts of pipeline ageing and damage.

Ensuring the accuracy of free-field inversion is crucial in determining seismic excitation for soil-structure interaction (SSI) systems. Due to the spherical and cylindrical diffusion properties of body waves and surface waves, the near-fault zone presents distinct free-field responses compared to the far-fault zone. Consequently, existing far-fault free-field inversion techniques are insufficient for providing accurate seismic excitation for SSI systems within the near-fault zone. To address this limitation, a tailored near-fault free-field inversion method based on a multi-objective optimization algorithm is proposed in this study. The proposed method establishes an inversion framework for both spherical body waves and cylindrical surface waves and then transforms the overdetermined problem in inversion process into an optimization problem. Within the multi-objective optimization model, objective functions are formulated by minimizing the three-component waveform differences between the observation point and the delayed reference point. Additionally, constraint conditions are determined based on the attenuation property of propagating seismic waves. The accuracy of the proposed method is then verified through near-fault wave motion characteristics and validated against real downhole recordings. Finally, the application of the proposed method is investigated, with emphasis on examining the impulsive property of underground motions and analyzing the seismic responses of SSI systems. The results show that the proposed method refines the theoretical framework of near-fault inversion and accurately restores the free-field characteristics, particularly the impulsive features of near-fault motions, thereby providing reliable excitation for seismic response assessments of SSI systems.

Hydraulic conductivity plays a significant role in the evolution of liquefaction phenomena induced by seismic loading, influencing the pore water pressure buildup and dissipation, as well as the associated settlement during and after liquefaction. Experimental evidence indicates that hydraulic conductivity varies significantly during and after seismic excitation. However, most previous studies have focused on experimentally capturing soil hydraulic conductivity variations during the post-shaking phase, primarily based on the results at the stage of excess pore water pressure dissipation and consolidation of sand particles after liquefaction. This paper aims to quantify the variation of hydraulic conductivity during liquefaction, covering both the co-seismic and postshaking phases. Adopting a fully coupled solid-fluid formulation (u-p), a new back-analysis methodology is introduced which allows the direct estimation of the hydraulic conductivity of a soil deposit during liquefaction based on centrifuge data or field measurements. Data from eight well-documented free-field dynamic centrifuge tests are then analysed, revealing key characteristics of the variation of hydraulic conductivity during liquefaction. The results show that hydraulic conductivity increases rapidly at the onset of seismic shaking but gradually decreases despite high pore pressures persisting. The depicted trends are explained using the KozenyCarman equation, which highlights the combined effects of seismic shaking-induced agitation, liquefaction, and solidification on soil hydraulic conductivity during the co-seismic and post-shaking phases.

This study presents a novel micromorphic continuum model for sand-gravel mixtures with low gravel contents, which explicitly accounts for the influences of the particle size distribution, gravel content, and fabric anisotropy. This model is rigorously formulated based on the principle of macro-microscopic energy conservation and Hamilton's variational principle, incorporating a systematic analysis of the kinematics of coarse and fine particles as well as macro-microscopic deformation differentials. Dispersion equations for plane waves are derived to elucidate wave propagation mechanisms. The results demonstrate that the model effectively captures normal dispersion characteristics and size-dependent effects on wave propagation in these mixtures. In long-wavelength regimes, wave velocities are governed by macroscopic properties, whereas decreasing wavelengths induce interparticle scattering and multiple reflections, attenuating velocities or inhibiting waves, especially when wavelengths approach interparticle spacing. The particle size, porosity, and stiffness ratio primarily influence the macroscopic average stiffness, exhibiting consistent effects on dispersion characteristics across all wavelength domains. In contrast, the particle size ratio and gravel content simultaneously influence both macroscopic mechanical properties and microstructural organization, leading to opposing trends across different wavelength ranges. Model validation against experiments confirms its exceptional predictive ability regarding wave propagation characteristics, including relationships between lowpass threshold frequency, porosity, wave velocity, and coarse particle content. This study provides a theoretical foundation for understanding wave propagation in sand-gravel mixtures and their engineering applications.

Buried pipelines are essential for the safe and efficient transportation of energy products such as oil, gas, and various chemical fluids. However, these pipelines are highly vulnerable to ground movements caused by geohazards such as seismic faults, landslide, liquefaction-induced lateral spreading, and soil creep, which can result in potential pipeline failures such as leaks or explosions. Response prediction of buried pipelines under such movements is critical for ensuring structural integrity, mitigating environmental risks, and avoiding costly disruptions. As such, this study adopts a Physics-Informed Neural Networks (PINNs) approach, integrated with a transfer learning technique, to predict structural response (e.g., strain) of both unreinforced and reinforced steel pipes subjected to Permanent Ground Displacement (PGD). The PINN method offers a meshless, simulation-free alternative to traditional numerical methods such as Finite Element Method (FEM) and Finite Difference Method (FDM), while eliminating the need for training data, unlike conventional machine learning approaches. The analyses can provide useful information for in-service pipe integrity assessment and reinforcement, if needed. The accuracy of the predicted results is verified against Finite Element (FE) and Finite Difference (FD) methods, showcasing the capability of PINNs in accurately predicting displacement and strain fields in pipelines under geohazard-induced ground movement.

Thallium sulphate (TLM) is a highly hazardous metal known to induce severe renal damage. Syringetin (SGN) is a naturally derived polyphenolic compound that demonstrates excellent medicinal properties. This research trial was conducted to determine the nephroprotective ability of SGN to inhibit TLM induced renal toxicity in rats by assessing different parameters including oxidative stress, apoptotic and inflammatory markers as well as histomorphological parameters. Thirty-two Sprague Dawley rats were apportioned into the control, TLM (6.4 mgkg- 1), TLM (6.4 mgkg- 1) + SGN (10 mgkg- 1) and SGN (10 mgkg- 1) alone administered group. Our findings revealed that TLM exposure promoted renal inflammation which was evident by increased mRNA expression of myeloid differentiation primary response 88 (MYD88), toll-like receptor 4 (TLR4), interleukin-1 beta (IL-1 beta), high mobility group box1 (HMGB1), tumor necrosis factor- alpha (TNF-alpha), receptor for advanced glycation end products (RAGE), cyclooxygenase-2 (COX-2), interleukin-6 (IL-6), and nuclear factor- kappa B (NF-kappa B). The concentrations of reactive oxygen species (ROS) and malondialdehyde (MDA) were exacerbated while the enzymatic action of heme oxygenase-1 (HO-1), superoxide dismutase (SOD), glutathione reductase (GSR), catalase (CAT), & tissue contents of glutathione (GSH) were reduced after TLM intoxication. Serum concentrations of N-Acetylglucosamine (NAG), blood urea nitrogen (BUN), Kidney Injury Molecule-1 (KIM-1), Neutrophil Gelatinase-Associated Lipocalin (NGAL), creatinine, uric acid were observed elevated while a notable reduction was noted in the concentration of creatinine clearance following the dose administration of TLM. The levels of Bcl-2-associated X protein (Bax), cysteine-aspartic acid protease-3 (Caspase-3) & cysteine-aspartic acid protease-9 (Caspase-9) were exacerbated while the concentration of B-cell lymphoma-2 (Bcl-2) was notably suppressed following regimen of TLM. Renal tissues were distorted after TLM administration. In contrast, SGN supplementation notably restored oxidative profile, reduced pro-inflammatory and apoptotic markers as well as improved renal histology.