Search Results (14,093)

Biosensors based on electrolyte-gated organic field-effect transistors (EGOFETs) have attracted considerable attention due to their advantages, including low cost, inherent signal amplification, and low-voltage operation. A critical step influencing sensing performance is the integration of specific receptors onto the device surface. Among various strategies, the covalent immobilization of biorecognition elements onto gold surfaces via thiol chemistry is one of the most widely used approaches. In this study, we report the optimization of a mixed self-assembled monolayer (SAM) composed of 11-mercaptoundecanoic acid (11-MUA) and 3-mercaptopropionic acid (3-MPA) for label-free detection of human IgG using EGOFETs. The quality of the SAM was systematically modulated by varying the total concentration from 10 to 400 mM and characterized using X-ray Photoelectron Spectroscopy (XPS), Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV), and Atomic Force Microscopy (AFM). The results revealed that a concentration of 50 mM yielded a densely packed and well-ordered monolayer. After covalent immobilization of anti-IgG antibodies via 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride/N-hydroxysuccinimide (EDC/NHS) chemistry and subsequent blocking with ethanolamine and bovine serum albumin (BSA), the functionalized gate electrodes were integrated into poly(3-hexylthiophene) (P3HT)-based EGOFETs. Electrical measurements demonstrated that EGOFET biosensors functionalized with the 50 mM SAM achieved optimal sensing performance. The devices exhibited a highly linear response (R² = 0.998) over a wide concentration range from 1 fM to 10 nM, with a LOD of 2.82 fM, and showed excellent selectivity against non-target immunoglobulins A and M (IgA and IgM). This SAM concentration optimization strategy provides a versatile approach for engineering high-performance EGOFET biosensors, with potential applicability to a broad range of disease biomarkers. Full article

Propolis produced by honeybees, Apis mellifera, has been valued since ancient times as a remedy for different ailments for its broad medicinal properties. This wide range of biological activities may arise from the production of distinct propolis types within the hive, each serving specific functions and containing unique molecular compositions. In this study, we investigated the effects of four propolis types—masonry, sealing, brood-protection, and intruder-neutralizing—on hydrogen peroxide (H₂O₂)-induced oxidative injury in human skeletal muscle cells. Among these, only brood-protection propolis significantly prevented the H₂O₂-induced loss of cell viability. Bio-guided fractionation of this active propolis identified five major compounds: benzyl caffeate (BC), caffeic acid phenethyl ester (CAPE), cinnamyl caffeate (CC), prenyl caffeate (PC), and (E)-3-methyl-3-butenyl caffeate (MBC), all displaying stronger cytoprotective effects than their ferulate equivalents. We finally demonstrated that propolis extract and its active compounds reduced lipid peroxidation in post-mortem minced mouse skeletal muscle and compared their efficacy to other natural compounds. Chemical analysis of resins from neighboring flora suggested that black poplar (Populus nigra) buds are the primary botanical source of these caffeate derivatives. Collectively, these results highlight the functional diversity of hive propolis and its potential applications in food preservation as well as in complementary and preventive medicine. Full article

Polymer-modified bituminous binders are widely used in road construction due to their enhanced mechanical performance; however, the effectiveness of these materials critically depends on the actual concentration of polymer modifiers, particularly styrene-butadiene-styrene (SBS). This study aims to develop and validate a rapid, reproducible Fourier Transform Infrared Spectroscopy—Attenuated Total Reflectance (FTIR-ATR) spectroscopy method for the quantitative determination of SBS content in polymer-modified bitumen (PMB). Since, to date, there is no clearly defined method for controlling the quantitative content of polymers in PMB, this creates difficulties in accepting the roadway into operation. Calibration PMB samples containing 1–4% SBS were prepared, tested for physical and mechanical properties, and analyzed spectroscopically to identify characteristic absorption bands at 966 cm⁻¹ and 699–760 cm⁻¹. A first-order calibration model was constructed to relate peak intensity to polymer concentration. The results demonstrate a clear linear correlation between SBS content and IR absorption features, confirming the suitability of FTIR as an instrumental method for routine laboratory control. Application of the model allowed determination of actual polymer mass fraction with high accuracy and reproducibility. The findings also showed that increased SBS levels improve softening point, elasticity, and low-temperature resistance, with 3–4% representing a performance-optimal range. Overall, the proposed FTIR-based approach provides an objective and efficient tool for quality control of polymer-modified binders and supports broader standardization efforts in the field. Full article

Precision agriculture has become a major direction of agricultural technological development in recent decades, addressing efficiency, environmental, and economic challenges simultaneously. Input optimization based on site-specific data collection—particularly variable-rate nutrient application, precision irrigation systems, and targeted crop protection—has been shown to generate measurable cost and resource savings. The aim of the study is to explore and systematically evaluate the economic impacts influencing precision technology in crop production. Although the technical and environmental benefits of precision technologies are widely documented, their economic performance and farm-level profitability remain inconsistently interpreted. The study is based on a systematic literature review of peer-reviewed English-language journal articles retrieved from the Web of Science, Scopus, ScienceDirect, and JSTOR databases. Study selection and evaluation were conducted in accordance with the PRISMA 2020 methodological framework. The literature indicates that precision technologies achieve average input savings of 8–20% and yield increases of 2–6%, while reported return on investment (ROI) values typically range between 5% and 15%. Economic viability is strongly dependent on farm size, with most studies identifying profitability above 100–200 ha. Additional benefits include improved management of soil heterogeneity, enhanced nutrient-use efficiency, and reduced excess input application, although adoption remains constrained by high investment costs and technological complexity. Full article

Electrospinning is the most widely used technique for creating nanofibers. However, the low production rate and the usage of a high-voltage setup have become obstacles to its widespread application. One effective method for creating nanofibers from a variety of materials is centrifugal spinning. This review discusses centrifugal spinning (CS) as an effective and scalable nanofiber manufacturing technology, particularly in filtration systems, and presents it as a promising alternative to existing methods, such as electrospinning. The review highlights the advantages of CS, including its high production rate, cost efficiency, and the ability to process various materials to produce nano- and microfibers. Despite its high potential, the issues associated with CS technology include the unpredictability of fiber quality, the inability to control diameters, and the need for more robust mathematical models to predict fiber characteristics. To eliminate these shortcomings and further enhance the industrial utility of centrifugally spun nanofibers in filtration, future studies should focus on improving process control, exploring a broader range of polymers, optimizing melt electrospinning, and designing more advanced nozzle profiles. Full article

Different methodologies have been developed for the analysis and study of dynamical systems, including both theoretical models and natural systems. Examples span a wide range of applications, such as astronomy, financial and economic time series, biophysical systems, physiological phenomena, and Earth sciences, including seismicity and climatic processes. The study of these complex systems is commonly based on the analysis of the signals they generate, using mathematical tools to extract relevant information. A broad spectrum of mathematical disciplines converges in this context, including stochastic, probability and statistical theory, entropic and informational measures, fractal and multifractal analysis, natural time analysis, modeling of non-linearity and recurrence methods, generalized entropies, non-extensive systems, machine learning, and high-dimensional and multivariate complexity. Research in this area is largely focused on the characterization of complex systems, providing indicators of determinism or stochasticity, distinguishing between regularity, chaos, and noise, and identifying topological as well as disorder-regularity features. In addition, short- and long-term forecasting, together with the identification of short- and long-range correlations, play a central role in such characterization. To address these objectives, numerous mathematical tools have been developed for the analysis of time series and point processes, each designed to capture specific signal properties. In this work, many of the most important tools used in time series analysis are compiled and reviewed, highlighting their main characteristics and the different types of complex systems to which they have been applied. Full article

Cyclodextrins (CDs) have gained increasing attention as versatile platforms for enhancing drug delivery to the central nervous system, particularly in overcoming the restrictive properties of the blood–brain barrier (BBB). Owing to their unique cyclic oligosaccharide structure, CDs are capable of forming inclusion complexes with a wide range of therapeutic agents, thereby improving their solubility, stability, and bioavailability. In addition to their role as excipients, growing evidence indicates that CDs can actively modulate biological processes, including membrane fluidity and cholesterol homeostasis, which are critical factors in neurological disorders. This review explores the application of CDs in facilitating drug transport across the BBB through multiple mechanisms, including carrier-mediated transport, receptor-mediated transcytosis, and nanoparticle-based delivery systems. Special emphasis is placed on their use in the treatment of neurodegenerative and neurological diseases, such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, Niemann–Pick type C disease, and other central nervous system disorders. In these contexts, CD-based formulations have demonstrated the ability to enhance brain targeting, reduce pathological protein aggregation, and improve therapeutic outcomes in preclinical models. This review uniquely integrates cyclodextrin’s physicochemical properties with specific blood–brain barrier transport mechanisms, proposing a structure–transport–therapy framework that enables a more predictive understanding of brain-targeted drug delivery. Full article

This study investigates the dripping and leakage problem in kitchenware known as the “teapot effect” through a multidisciplinary experimental approach encompassing fluid mechanics, material science, and ergonomic design. Unlike previous studies confined to idealized geometries and single-fluid analyses, this work systematically examines 32 distinct spout geometries from commercially available teapots, coffee pots, and milk jugs under realistic operating conditions. Experiments were performed using three fluids with contrasting rheological properties: boiling black tea, cow’s milk, and Turkish coffee on a precision rotating platform operating at quasi-static (1°/s) to isolate surface tension, gravitational, and geometric effects from inertial forces. Three quantitative parameters were measured for each specimen: capillary dome angle, teapot effect angle range, and optimum pouring angle. Results demonstrate that spout tip geometry is the dominant controlling parameter. Thin-lipped elliptical cross-sections effectively suppressed dripping, whereas triangular and wide curved geometries produced the teapot effect across broad pouring angle ranges reaching up to 70°. A spout outlet extension length of 4–5 mm combined with a spout tip radius below 4 mm was found necessary and sufficient for clean flow separation. Furthermore, suspended particles and proteins in milk and Turkish coffee were shown to intensify the teapot effect by disrupting contact line dynamics at the spout tip. These findings provide quantitative design thresholds directly applicable to industrial kitchenware development. Full article

This paper demonstrates a C-band continuously tunable mode-locked fiber laser based on a carbon nanotube saturable absorber (CNT-SA) and a commercial broadband tunable filter. The laser operates in the C-band with a continuous tuning range of 37.3 nm from 1532.6 nm to 1569.9 nm. The erbium-doped fiber (EDF) has a wide gain range, enabling the laser to achieve ultrafast mode-locking. Meanwhile, the tunable filter offers a broad wavelength selection range. This continuously tunable mode-locked fiber laser features a simple structure and a broad operating wavelength range, making it highly suitable for applications in optical communication, sensing, and laser processing. Full article

Compost is widely used to improve soil fertility and structure, yet its effects on soil physical properties in Vertosols remain insufficiently documented. This study evaluated the effects of repeat compost application on soil carbon and nitrogen contents and selected soil physical properties in Vertosols from three farms in Queensland, Australia (Roma, Dalby, and Goovigen). Compost had been applied at rates between 5 and 22 Mg ha⁻¹ yr⁻¹ for periods ranging from 3 to 11 years, depending on the site. Intact and disturbed soil samples from the top 0–8 cm were analyzed for bulk density, water retention, hydraulic properties, aggregate stability, and water repellence. Aggregate stability was assessed using laser diffraction before and after ultrasonic dispersion. Compost application significantly increased total carbon and nitrogen contents at all sites (p ≤ 0.01), although effects on soil physical properties varied by site. In Dalby, compost improved water retention and aggregate stability; in Goovigen, it resulted in lower Disaggregation Ratios. Compost did not induce soil water repellence at any site. The results indicate that compost amendments improve soil carbon and nitrogen concentrations and can modify soil physical properties in Vertosols, although responses depend on site conditions and management history. Full article

An important challenge for materials researchers in the modern era is the fabrication of high-performance electrodes with novel designs and structures to enhance electrochemical sensing and energy storage performance. Recently, perovskite-structured bimetallic hydroxide materials, owing to their high conductivity, decent surface area, abundant redox activity, and good stability, have emerged as promising candidates for bifunctional electrochemical applications. In this study, we designed perovskite-type CuSn(OH)₆ microspheres via a facile coprecipitation method for nifedipine (NFD) sensing and supercapacitors (SCs). Various characterization techniques were employed to confirm the successful synthesis of CuSn(OH)₆. The uniform formation and distribution of CuSn(OH)₆ within the sphere structure provide rich reactive sites and enhance structural stability, thereby improving electrochemical activity. This architecture also induces a synergistic effect between Cu and Sn, which increases conductivity and accelerates redox kinetics. Consequently, the electrode modified with CuSn(OH)₆/GCE exhibited a wide linear concentration range of 0.4–303.3 µM and a low detection limit of 0.44 µM for NFD detection. This sensor further demonstrated superior analytical reliability, with selectivity of <5%, cycling stability of 84.79%, reproducibility of 3.3%, and recovery rates of 99.2–99.8% in the serum sample. Concurrently, the CuSn(OH)₆/NF showcased a high specific capacitance of 514 F g⁻¹ at 1 A g⁻¹, good longevity of 83.05% retention after 5000 cycles, and low charge transfer resistance of 6.56 Ω and solution resistance of 1.04 Ω, validating fast ion–electron transport. These results underscore that perovskite-based CuSn(OH)₆ is an efficient dual-functional electrocatalyst for sensitive electrochemical detection and high-performance SCs. Full article

Electrophoresis titration sensors are widely used for biomarker detection. However, traditional methods rely on a visible boundary for signal readout. Although conventional capacitively coupled contactless conductivity detection avoids indicator dependence, its single-point detection method suffers from long measurement times, large amounts of redundant data, and the inability to dynamically monitor the moving reaction boundary. To address these issues, we developed a novel contactless scanning capacitively coupled conductivity-detection method for microchip electrophoretic titration sensors. This method enables the rapid tracking and monitoring of the boundary within the microfluidic channel through dynamic scanning. The spatial distribution of conductivity during electrophoretic titration was theoretically analyzed. To evaluate the method, glucose was chosen as a model analyte. Quantitative detection was achieved over the linear range of 0.2–50 mM, with the limit of detection of 0.1 mM. The method exhibited satisfactory stability with relative standard deviation values ranging from 0.9% to 4.3% (n = 3). While the detection limit is higher than optical methods (0.02 mM), the results confirmed that the novel method offers merits, such as compact size, low cost and label-free operation. Moreover, it demonstrated strong potential for portable, quantitative analysis of target analytes across a wide range of applications. Full article

Coherent Raman scattering (CRS) techniques such as coherent anti-Stokes Raman scattering (CARS) provide chemically specific vibrational contrast with signal levels far exceeding spontaneous Raman scattering (SpRS). Extending these to broadband excitation enables multiplex detection across wide spectral regions, including the fingerprint region, CH-stretch bands and high-frequency vibrational modes. This review provides a structured overview of excitation architecture for broadband CRS, ranging from low-energy oscillator schemes to energy-scalable platforms. The discussion is organized along key design parameters, including spectral bandwidth, excitation intensity, and probe delay, which jointly determine the accessible operating regimes. Rather than representing competing methods, the reviewed architectures are presented as a complementary toolbox for application-driven spectroscopy in chemically reactive environments and complex biological systems. In addition, a representative OPCPA-based implementation is presented as a platform demonstration to illustrate accessible operating regimes, single-shot stability, and multiplex detection capability under realistic experimental conditions. Full article

As the demand for sustainable and bio-based alternatives to petroleum-derived membranes grows, polysaccharides have emerged as promising candidates. In this study, we fabricated free-standing membranes from konjac glucomannan (KGM), a neutral polysaccharide, using a simple base-induced insolubilization process. Fourier transform infrared spectroscopy revealed that the deacetylation of KGM chains promotes extensive intermolecular hydrogen bonding, creating a robust and stable three-dimensional network without the need for chemical cross-linkers. The resulting KGM free-standing membranes exhibited excellent mechanical properties, characterized by high tensile strength in the dry state and remarkable flexibility when hydrated. Furthermore, the membranes demonstrated superior chemical resistance to organic solvents such as acetone and n-hexane. Transport studies showed that the membranes possess a highly dense structure with no detectable pressure-driven pure-water permeation up to 0.25 MPa. Solute permeation experiments using eight model molecules (molecular weight = 144–14,600 Da) indicated that transport behavior is consistent with diffusion through a hydrated polymer network. The effective diffusion coefficient D_eff showed a strong correlation with molecular weight M, following the relationship D_eff ∝ M^−1.7. Furthermore, the permeation behavior remained stable across a wide pH range (2–12), and, within the investigated range of monovalent solutes, D_eff was insensitive to solute charge, indicating that mass transport is dominated by size-based diffusion rather than electrostatic interactions. These findings suggest that KGM free-standing membranes enable reliable molecular fractionation based on size-dependent diffusion within a stable, neutral matrix, offering significant potential for sustainable separation technologies and biomedical applications. Full article

Distributed acoustic sensing (DAS) has been widely applied to injection–production profile monitoring in horizontal wells because it provides continuous full-wellbore coverage, real-time acquisition, and straightforward long-term deployment. In practical downhole operations, however, DAS measurements are frequently compromised by optical-signal attenuation, loss of fiber–casing/formation coupling, and environmental noise. Meanwhile, the mechanisms governing flow-induced acoustic responses remain insufficiently understood, which continues to impede quantitative diagnosis and interpretation of injection–production profiles based on DAS data. To address these challenges, this study performed controlled laboratory-scale physical simulation experiments of single-phase flow in a horizontal wellbore, systematically investigating DAS acoustic responses under two wellbore diameters (25 mm and 50 mm) and a range of flow velocities. Power spectral density (PSD) was derived using the fast Fourier transform to identify flow-sensitive characteristic frequency bands, and frequency-band energy (FBE) was further used to establish an optimal quantitative relationship with flow velocity. The results show that: (1) DAS energy is dominated by low-frequency components (<100 Hz), with the total energy increasing nonlinearly as flow velocity rises, accompanied by a progressive broadening of the characteristic bands; (2) the feature bands identified using an adaptive method based on energy difference statistics applied to PSD frequency-domain features exhibit a higher signal-to-noise ratio and greater physical clarity than traditional wide frequency bands; furthermore, by employing a feature band merging strategy, the distribution characteristics of flow energy can be captured more comprehensively; and (3) FBE exhibits a strong nonlinear dependence on flow velocity, with a power-law model delivering the best theoretical fit, whereas a cubic model (FBE ∝ V³) achieves high accuracy and robustness for practical applications. The proposed workflow—“PSD peak identification–characteristic band delineation–FBE regression”—establishes a methodological foundation for quantitative DAS-based monitoring of horizontal-well injection–production profiles in both laboratory and field settings, and it provides a basis for subsequent intelligent monitoring and interpretation under multiphase-flow conditions. Full article