This study presents a comprehensive investigation of polyimide (PMDA-ODA) nanocomposite membranes incorporating hematite (Fe 2 O 3 ) and magnetite (Fe 3 O 4 ) nanoparticles. Incorporation of these fillers primarily aims to reduce nitrogen permeability by reducing the adsorption of this gas on the membrane surface, thereby enhancing membrane selectivity for the CO 2 /N 2 system. The gas separation performance was evaluated using pure CO 2 and N 2 permeation tests, which systematically determined key transport parameters, including permeability, diffusion coefficients, solubility coefficients, and ideal selectivity. The optimal filler content was identified as 5 wt% for Fe 2 O 3 and 2 wt% for Fe 3 O 4 , achieving the highest ideal selectivity values of 76.45 and 98.08, respectively. At these loadings, the corresponding CO 2 permeabilities were 2.60 and 3.07 Barrer. The principal novelty of this work is the introduction and comprehensive investigation of a gas-transport mechanism referred as differential-sorption, which has been applied for mixed matrix membranes for the first time. The transport model was developed to better understand the transport behaviour depending on filler type and loading in polymer matrix. A fundamental assumption of this mechanism is limited sorption of one studied gases, while the second gas transport is stabilized by improved interactions with filler and Knudsen diffusion in magnetic channels. The model accuracy was confirmed through random-walk simulations and benchmarked against experimental results and classical predictions from the Maxwell and Bruggeman models. The strong agreement between the model and experimental data was further supported by detailed structural and property analyses, including thermogravimetric analysis, scanning electron microscopy, atomic force microscopy, gas sorption studies, and mechanical and magnetic measurements.
ABSTRACT Procalcitonin (PCT) serves as a valuable yet challenging biomarker for bacterial infections, with conventional detection methods constrained by prolonged assay durations. Electrochemical techniques provide a faster and more straightforward alternative, though they face challenges such as electrode fouling and limited sensitivity and selectivity. To address these issues, we developed a sensor using highly conductive 2D material, i.e. Ti3C2Tx MXene combined with poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), serving as an ideal microenvironment for the direct immobilization of PCT antibody, with a bovine serum albumin (BSA) coating to provide antifouling activity. The resulting BSA/Ab‐PEDOT:PSS/MXene‐based sensor is characterized with a wide PCT detection range (25–250 pg mL−1) and gained low detection limit (4.4 pg mL−1). The sensor shows promise as a rapid, simple tool for diagnosing bacterial infections or sepsis, enabling timely diagnosis and improved patient outcomes.
The rising demand for sustainable pest management has increased interest in plant-derived biopesticides as environmentally friendly alternatives to synthetic insecticides. This research assessed the insecticidal potential of Melia azedarach leaf extract (MLE) against Galleria mellonella larvae through comprehensive phytochemical, toxicological and physiological analyses. Phytochemical screening indicated substantial polyphenolic content with total phenolic (42.06 +/- 1.12 mg GAE/g), flavonoid (16.96 +/- 1.42 mg QE/g) and condensed tannin (9.46 +/- 0.49 mg CE/g) contents. High-performance liquid chromatography (HPLC) analysis detected 16 phenolic and flavonoid substances, with kaempferol and quercetin as major constituents. Acute toxicity assessment via ingestion demonstrated dose-dependent mortality with an LD50/10 days of 1.39 mg g-1 body weight. Sublethal exposure (LD25) markedly disrupted developmental parameters, prolonging larval and pupal development and diminishing pupal weight and fecundity. All investigated midgut enzymes showed significant activity decline, with lysozyme exhibiting the most pronounced reduction (68.13%); carbohydrate digestive enzyme activity (alpha-amylase, alpha-glucosidase, beta-glucosidase, beta-galactosidase) reduced in the range of 42%-60%, while protein digestive enzyme activity (trypsin, chymotrypsin, carboxypeptidase, cysteine protease, leucine aminopeptidase) reduction was in the range of 34%-53%. Histological and ultrastructural analyses demonstrated extensive midgut epithelial damage, including vacuolization, cellular degeneration and microvilli disruption. Thus, M. azedarach seems to possess a battery of insecticidal mechanisms that establish it as an eco-friendly biocontrol agent under integrated pest management strategies.
Ranikhola River Sub-Basin features a complex topography and frequent landslides. Road construction and urban expansion exacerbate the situation. Multi-criteria decision-making (MCDM) and machine learning methods are used to assess spatial landslides in the Ranikhola River Sub-Basin, East Sikkim. Thirteen landslide conditioning factors were represented as GIS layers in the study area to construct landslide susceptibility maps. Parameters were assigned weights using the Analytic Hierarchy Process (AHP) and Entropy methods to balance subjective and objective influences. Random forests (RFs) and artificial neural networks (ANNs) were compared with two MCDM methods, TOPSIS and VIKOR, to map landslide susceptibility. The dataset was divided into training and testing, with a 70:30 ratio. As shown by accuracy assessments, ML approaches outperform MCDM. Slope (23.21
The structural integrity of isolation dams in deep coal mines is critical to preventing underground disasters, particularly those involving water and waste-mixture inrushes. This study presents a forensic root-cause analysis, using reverse-engineering techniques, of a specific isolation-dam rupture to determine the failure mechanism under complex stress conditions and limited data availability. A hybrid investigative methodology was employed, combining sequential post-failure documentation analysis with physical-scale modelling and numerical simulations to reconstruct a deadly disaster for criminal investigation purposes. A 1:5 scale physical model of the excavation and dam was constructed using original construction materials to test the structure's resistance to hydrostatic pressure. The experimental results demonstrated that the dam maintained integrity under static hydraulic loads representative of real-world conditions, with only minor seepage ("sweating") and no structural failure over a 7-day monitoring period. To investigate external geomechanical factors, Finite Element Method (FEM) simulations were conducted using ANSYS software. The numerical analysis evaluated the effects of rock mass pressure and convergence on the dam's stability. The results indicate that while the dam was designed to withstand significant hydraulic head, the failure was precipitated by excessive rock mass pressure at a depth of around 600 m, which induced critical stress concentrations exceeding the masonry's load-bearing capacity. This study confirms that the dynamic rupture was driven by unforeseen geomechanical forces rather than hydrostatic overload alone, highlighting the necessity of considering rock mass-structure interaction in the safety assessment of underground isolation barriers. This approach enables mutual verification of the results obtained and reduces the ambiguity of interpretation that often accompanies the analysis of accident events in underground mining. It also confirms the application of tested methodology for mining disaster reconstruction as proof at the stage of investigation and in the Court.
