Search Results (2,048)

The rising demand for sustainable agriculture and circular resource management has intensified interest in converting wastewater sludge into value-added products. This review explores the transformation of sewage sludge into slow- and controlled-release fertilizers (CRFs), with a focus on biochar production and encapsulation technologies. Sewage sludge is rich in essential macronutrients (N, P, K), micronutrients, and organic matter, making it a promising feedstock for agricultural applications. However, its use is constrained by challenges including compositional variability, presence of heavy metals, pathogens, and emerging contaminants such as microplastics and PFAS (Per- and Polyfluoroalkyl Substances). The manuscript discusses a range of stabilization and conversion techniques, such as composting, anaerobic digestion, pyrolysis, hydrothermal carbonization, and nutrient recovery from incinerated sludge ash. Special emphasis is placed on coating and encapsulation technologies that regulate nutrient release, improve fertilizer efficiency, and reduce environmental losses. The role of natural, synthetic, and biodegradable polymers in enhancing release mechanisms is analyzed in the context of agricultural performance and soil health. While these technologies offer environmental and agronomic benefits, large-scale adoption is hindered by technical, economic, and regulatory barriers. The review highlights key challenges and outlines future perspectives, including the need for advanced coating materials, improved contaminant mitigation strategies, harmonized regulations, and field-scale validation of CRFs. Overall, the valorisation of sewage sludge into CRFs presents a viable strategy for nutrient recovery, waste minimization, and sustainable food production. With continued innovation and policy support, sludge-based fertilizers can become a critical component of the green transition in agriculture. Full article

This study presents the results of research on the pelleting process of pine sawdust with the addition of cherry stone waste, which was carried out using a flat-die pellet press in the context of fuel pellet production. The findings indicate that increasing the proportion of crushed cherry stones in the sawdust mixture from 10% to 20% reduced the pelletizer’s power demand by approximately 14% (from 3.35 to 2.86 kW) and by around 24% (from 3.79 to 2.86 kW), compared with the compaction of sawdust alone. The incorporation of 10% crushed cherry stone waste into pine sawdust slightly improved the kinetic strength of the pellets, increasing it by about 2% (from 94.6 to 96.60%). However, raising the cherry stone content further to 20% resulted in a moderate decrease in kinetic strength, by approximately 5% (from 96.60 to 91.37%). A similar trend was observed for pellet density: the addition of cherry stones (10–20%) slightly reduced the density by about 5.5% (from 1312.02 to 1241.65 kg·m⁻³), accompanied by a small decrease in bulk density. This study also confirmed the high calorific potential of crushed cherry stones, with a heat of combustion of 24.418 MJ·kg⁻¹ (dry basis) and a net calorific value of 22.326 MJ·kg⁻¹. Their incorporation at levels of 10–20% into sawdust mixtures increased the heat of combustion of the pellets by 0.42–0.84% (from 19.959 MJ·kg⁻¹ for sawdust alone at 15% moisture content to 20.042 MJ·kg⁻¹ with a 10% addition and 20.126 MJ·kg⁻¹ with a 20% addition). Moreover, the inclusion of cherry stone waste in the mixture had a beneficial effect on combustion performance, lowering emissions of harmful compounds such as CO, NO, and SO₂, due to the higher combustion temperature achieved. Consequently, the use of cherry stone waste as an additive to sawdust not only enhances the energetic and environmental performance of pellets but also provides an effective pathway for the management of large quantities of fruit industry residues. Full article

Mathematical creativity (MC) plays an important role in mathematics and education; however, its conceptualization and assessment remain inconsistent across empirical studies. This systematic review examined how MC has been defined, conceptualized, and assessed across 80 empirical studies involving K-12 populations. Through thematic analysis, the study identified three definition types: divergent thinking, problem-solving, and problem-posing, as well as affective–motivational emphasis. We organized theoretical frameworks into three categories: domain-general, domain-specific, and multidimensional frameworks. Results showed that the most common definitions emphasized divergent thinking components while fewer studies highlighted affective and dispositional factors. Domain-specific frameworks were the most frequently used, followed by multidimensional frameworks. Regarding assessment, studies predominantly relied on divergent-thinking scoring. Most assessments used criterion-referenced rubrics with norm-based comparisons. They were delivered mainly in paper-pencil format. Tasks were typically open-ended multiple-solution problems with fewer studies using self-reports or observational methods. Overall, the field prioritizes product-based scoring (e.g., fluency, flexibility, originality) over evidence about students’ solution processes (e.g., reasoning, metacognitive monitoring). To improve cross-context comparability, future work should standardize and transparently report age, grade, and country coding and scoring practices. Full article

In the context of climate change and energy transition, the growing frequency of extreme weather events threatens the safety and stability of power systems. Given the limitations of existing research on load characteristic analysis and load forecasting during extreme weather events, this paper proposes a load-integrated forecasting model that accounts for extreme weather. First, an improved power load clustering method is proposed, combining Kernel PCA for nonlinear dimensionality reduction and an enhanced k-means algorithm, enabling both qualitative analysis and quantitative representation of load characteristics under extreme weather. Second, an optimal combination forecasting model is developed, integrating improved SVM and enhanced LSTM networks. Building upon the improved power load clustering algorithm, a load-integrated forecasting model considering extreme weather is established. Finally, based on the proposed load-integrated forecasting model, a time-series production simulation model considering extreme weather is constructed to quantitatively analyze the power and electricity balance risks of the system. Case studies demonstrate that the proposed integrated forecasting model can effectively analyze load characteristics under extreme weather and achieve more accurate load forecasting, which can provide guidance for the planning and operation of new power systems under extreme weather conditions. Full article

The purpose of this study is to propose and critically assess a sustainable urban regeneration model for the redevelopment of the former K-2 military airbase in Daegu, Korea. Large-scale idle military sites pose significant challenges in terms of ecological remediation, social integration, and economic transformation, but also offer opportunities for redefining urban identity and global competitiveness. To address this, we develop the concept of the “Global Contents City,” a planning framework that integrates cultural exchange, creative industries, education, and tourism within a sustainable urban ecosystem. The research employs a qualitative methodology that combines theoretical review, comparative analysis of international precedents (e.g., Munich-Riem, Tempelhof, Stapleton, and Toronto), and design-oriented masterplanning. The findings highlight design strategies that spatially interconnect cultural, educational, industrial, and ecological functions while reinforcing low-carbon infrastructure and green open space. By situating the Daegu K-2 case in an international context, the study demonstrates how lessons from post-military redevelopments can be adapted to Korea, contributing to both scholarly debates and practical frameworks for sustainable city-making. Full article

The SETD6 protein lysine methyltransferase monomethylates specific lysine residues in a diverse set of substrates which contain the target lysine residue in a highly variable amino acid sequence context. To investigate the mechanism underlying this multispecificity, we analyzed SETD6 substrate recognition using AlphaFold 3 docking and peptide SPOT array methylation experiments. Structural modeling of the SETD6–E2F1 complex suggested that substrate binding alone is insufficient to restrict SETD6 activity to only one lysine residue, pointing to additional sequence readout at the target site. Methylation of mutational scanning peptide SPOT arrays derived from four different SETD6 substrates (E2F1 K117, H2A.Z K7, RELA K310, and H4 K12) revealed sequence preferences of SETD6 at positions −1, +2, and +3 relative to the target lysine. Notably, glycine or large aliphatic residues were favored at −1, isoleucine/valine at +2, and lysine at +3. These preferences, however, were sequence context dependent and variably exploited among different substrates, indicating conformational variability of the enzyme–substrate interface. Mutation of SETD6 residue L260, which forms a contact with the +2 site in the available SETD6-RELA structure, further demonstrated substrate-specific differences in recognition at the +2/+3 sites. Together, these findings reveal a versatile mode of peptide recognition in which the readout of each substrate position depends on the overall substrate peptide sequence. These findings can explain the multispecificity of SETD6 and similar mechanisms may underlie substrate selection in other protein methyltransferases. Full article

Coating degradation monitoring is increasingly important in offshore industries, where protective layers ensure corrosion prevention and structural integrity. In this context, coating thickness estimation provides critical information. The ultrasound pulse-echo technique is widely used for non-destructive testing (NDT), but closely spaced acoustic interfaces often produce overlapping echoes, which complicates detection and accurate isolation of each layer’s thickness. In this study, analysis of the pulse-echo signal from a coated sample has shown that the front-coating reflection affects each main backwall echo differently; by comparing two consecutive backwall echoes, we can cancel the acquisition system’s impulse response and isolate the propagation path-related information between the echoes. This work introduces an ultrasound echo-based methodology for estimating coating thickness by first obtaining the impulse response of the test medium (reflectivity sequence) through a deconvolution model, developed using two consecutive backwall echoes. This is followed by an enhanced detection of coating layer thickness in the reflectivity function using a 1D convolutional neural network (1D-CNN) trained with synthetic signals obtained from finite-difference time-domain (FDTD) simulations with k-Wave MATLAB toolbox (v1.4.0). The proposed approach estimates the front-side coating thickness in steel samples coated on both sides, with coating layers ranging from $60\mathsf{\mu }$m to $740\mathsf{\mu }$m applied over 5 mm substrates and under varying coating and steel properties. The minimum detectable thickness corresponds to approximately $\mathit{\lambda }/5$ for an 8 MHz ultrasonic transducer. On synthetic signals, where the true coating thickness and speed of sound are known, the model achieves an accuracy of approximately $8\mathsf{\mu }$m. These findings highlight the strong potential of the model for reliably monitoring relative thickness changes across a wide range of coatings in real samples. Full article

The intrinsic noise of giant magnetoresistive (GMR) sensors is large at low frequencies, and their resolution is inevitably significantly limited. Investigation of GMR noise requires the use of measurement systems that have lower noise than the sample. In this context, the main purpose of this study is to evaluate the effectiveness of two electronic noise measurement configurations of a single GMR sensing element. The first method connects the sample in a voltage divider configuration and the second method connects in a Wheatstone bridge configuration. Three amplification set-ups were investigated: a low-noise amplifier, an ultra-low-noise amplifier and an instrumentation amplifier. Using cross-correlation, the noise of the measurement system introduced by the amplifiers was reduced. Noise spectra were recorded at room temperature in the frequency range of 0.5 Hz to 10 kHz, under different sample bias voltages. The measurements were performed in zero applied magnetic field and in a field corresponding to the maximum sensitivity of the sensor. From the noise spectra, the detectivity of the sensor was determined to be in the 200–300 nT/√Hz range. Good agreement was observed between the results obtained using all three set-ups, suggesting the effectiveness of the noise measurement systems applied to the magnetoresistive sensor. Full article

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) nucleases enable precise genome editing, but off-target cleavage remains a critical challenge. Here, we report the development of MAD7_HF, a high-fidelity variant of the MAD7 nuclease engineered through a bacterial screening system leveraging the DNA gyrase-targeting toxic gene ccdB. This system couples survival to efficient on-target cleavage and minimal off-target activity, mimicking the transient action required for high-precision editing. Through iterative selection and sequencing validation, we identified MAD7_HF, harboring three substitutions (R187C, S350T, K1019N) that enhanced discrimination between on- and off-target sites. In Escherichia coli assays, MAD7_HF exhibited a >20-fold reduction in off-target cleavage across multiple mismatch contexts while maintaining on-target efficiency comparable to wild-type MAD7. Structural modeling revealed that these mutations stabilize the guide RNA-DNA hybrid at on-target sites and weaken interactions with mismatched sequences. This work establishes a high-throughput bacterial screening strategy that allows the identification of Cas12a variants with improved specificity at a given target site, providing a useful framework for future efforts to develop precision genome-editing tools. Full article

This study evaluates the impact of different territorial contexts on academic mobility within the framework of the Erasmus Programme, using data on Key Action 1 exchanges between 2015 and 2023. Using official EU datasets and a gravity model framework, the research investigates how economic performance, geographical distance, EU membership, AUF (Agence Universitaire de la Francophonie) regional affiliation, and state contiguity shape international academic flows. The research developed two gravity models: one aimed to measure the potential barriers to academic flows through a residuals analysis, and the second integrated territorial delineations as predictors. In both models, the core of the explanatory variable is formed by indicators describing the economic performance of states and the distance between countries. When applied, the models converge in emphasizing that the inclusion of states in different territorial configurations has a strong effect on the structuring of academic flows. This suggests that the Erasmus Programme exhibits trends of overconcentration of flows in a limited number of countries, questioning the need for a more polycentric strategy and a reshaping of the funding mechanisms. Even if the gravity models behave well, given the limited number of predictors, further studies may need to incorporate qualitative indicators for a more comprehensive evaluation of the interactions. Full article

Background and Clinical Significance: In hepatocellular carcinoma (HCC), numerous signaling pathways become aberrantly regulated, resulting in sustained cellular proliferation and enhanced metastatic potential. Tumors that lack PYGO2 may not show the same types of tissue remodeling or regenerative features driven by the Wnt/β-catenin pathway, which could make the tumor behave differently from others that are Wnt-positive. PIK3CA-positive tumors are often associated with worse prognosis due to the aggressive nature of the PI3K/AKT pathway activation. This is linked to higher chances of metastasis, recurrence, and resistance to therapies that do not target this pathway. Case presentation: In this paper we present a rare case of hepatocellular carcinoma with PIK3CA-positive and PYGO2-negative signaling pathways, several key aspects of the tumor’s behavior, prognosis, and treatment options. Although alpha-fetoprotein (AFP) levels were significantly elevated, the CT and MRI examination showed characteristics of malignancy, HCC with secondary hepatic lesions and associated perfusion disturbances. The case particularities and immunohistochemistry features are highlighted in the context of literature review, the PIK3CA mutation suggesting the activation of the PI3K/AKT/mTOR pathway, a critical signaling pathway involved in cell survival, proliferation, and metabolism. Conclusions: Due to the aggressive nature of PIK3CA mutations, close monitoring and consideration of immunotherapy and targeted treatments are of crucial importance. Full article

Antibody-free nucleic acid lateral flow assays (AF-NALFA) are an established approach for rapid detection of amplified pathogens DNA but can yield inconsistent signals across targets. Since AF-NALFA depends on dual hybridization of probes to single-stranded amplicons (ssDNA), site-specific thermodynamic (Gibbs free energy-ΔG) at probe-binding regions may be crucial for performance. This study investigated how site-specific-ΔG and sequence complementarity at probe-binding regions determine Test-line signal generation, comparing native and synthetic amplicons and assessing the effects of local secondary structures and mismatches. Asymmetric PCR-generated ssDNA amplicons of Listeria monocytogenes, Mycobacterium leprae, and Leishmania amazonensis were analyzed in silico and tested in AF-NALFA prototypes with gold-labeled thiol probes and biotinylated capture probes. T-line signals were photographed, quantified (ImageJ version 1.4k), and statistically correlated with site-specific-ΔG. While native ssDNA from M. leprae and L. amazonensis failed to produce AF-NALFA T-line signals, L. monocytogenes yielded strong detection. Site-specific-ΔG below −10 kcal/mol correlated with reduced hybridization. Synthetic oligos preserved signals despite structural constraints, whereas ~3–4 mismatches, especially at capture probe regions, markedly impaired T-line intensity. The performance of AF-NALFA depends on the synergism between thermodynamic accessibility, site-specific-ΔG-induced site constraints, and sequence complementarity. Because genomic context affects hybridization, target-specific thermodynamic in silico evaluation is necessary for reliable pathogen DNA detection. Full article

Lung-protective ventilation and other experimental conditions raise arterial carbon dioxide tension (PaCO₂) and alter pH. Short-term benefits are reported in non-infectious settings, whereas infection and/or prolonged exposure are typically harmful. This scoping review systematically maps immune-mediated effects of hypercapnia on innate immunity and alveolar epithelial repair. Scoping review per Levac et al. and PRISMA Extension for Scoping Reviews (Open Science Framework protocol: 10.17605/OSF.IO/WV85T; post hoc). We searched original preclinical studies (in vivo/in vitro) in PubMed, Web of Science, ScienceDirect, Cochrane Reviews, and SciELO (2008–2023). PaCO₂ (mmHg) was prioritized; %Fraction of inspired Carbon Dioxide (%FiCO₂) was recorded when PaCO₂ was unavailable; pH was classified as buffered/unbuffered. Data were organized by context, PaCO₂, and exposure duration; synthesis used heat maps (0–120 h) and a narrative description for >120 h. Mechanistic axes extracted the following: NF-κB (canonical/non-canonical), Bcl-2/Bcl-xL–Beclin-1/autophagy, AMPK/PKA/CaMKKβ/ERK1/2 and ENaC/Na,K-ATPase trafficking, Wnt/β-catenin in AT2 cells, and miR-183/IDH2/ATP. Thirty-five studies met the inclusion criteria. In non-infectious models, a “protective window” emerged, with moderate PaCO₂ and brief exposure (65–95 mmHg; ≤4–6 h), featuring NF-κB attenuation and preserved epithelial ion transport. In infectious models and/or with prolonged exposure or higher PaCO₂, harmful signals predominated: reduced phagocytosis/autophagy (Bcl-2/Bcl-xL–Beclin-1 axis), AMPK/PKA/ERK1/2-mediated internalization of ENaC/Na,K-ATPase, depressed β-catenin signaling in AT2 cells, impaired alveolar fluid clearance, and increased bacterial burden. Chronic exposures (>120 h) reinforced injury. Hypercapnia is a context-, dose-, time-, and pH-dependent double-edged modulator. The safe window is narrow; standardized, parallel reporting of PaCO₂ and pH—with explicit comparisons of buffered vs. unbuffered hypercapnia—is essential to guide clinical translation. Full article

Cave systems are a kind of natural laboratory for interdisciplinary research on karstogenesis in the context of global changes. In this study, we investigate the concentration of ²²²Rn at 65 points in 37 representative caves of Bulgarian karst through continuous monitoring with passive and active detectors with a duration of 1 to 13 years. The concentration changes strongly both in the long term and seasonally, with values from 0.1 to 13 kBq m⁻³. These variations are analyzed from different perspectives (location and morphological features of the cave system, cave climate, ventilation regime, etc.). The seasonal change in the direction and intensity of ventilation is a leading factor determining the gas composition of the cave atmosphere during the year. Parallel measurements of ²²²Rn and CO₂ concentrations in the cave air show that both gases have a similar seasonal fluctuation. Cases of coincidences of an anomalous increase in the concentration of ²²²Rn with manifestations of seismic activity and micro-displacements along tectonic cracks in the caves have also been registered. The dependencies between the ²²²Rn concentration in the caves and in the soil above them are also discussed, as well as the possible connections between global trends in climate change and trends in ²²²Rn emissions. Special attention is paid to the risks of radiation exposure in show caves. A calculation procedure has been developed to achieve the realistic assessment of the effective dose of cave guides. It is based on information about the annual course of the ²²²Rn concentration in the respective cave and the time schedule of the guides’ stay in it. The calculation showed that the effective dose may exceed the permitted limits, and it is thus necessary to control it. Full article

Drug delivery is a well-established method for transporting anticancer drugs to cancerous tumors while minimizing damage to surrounding healthy tissues. Carbon nanocapsules (CNs) and boron nitride nanocapsules (BNNs) are promising nanocarriers capable of delivering drugs to tumor sites following their release. In this context, their diffusivity characteristics and drug release behavior need to be thoroughly addressed. This study examines the diffusion mechanisms of CNs and BNNs, as well as the impact of nanobubble cavitation on their performance as drug-releasing agents, utilizing molecular dynamics (MD) simulation methods. The results revealed that BNNs exhibit a higher diffusion coefficient compared to CNs in pure water. Moreover, temperature cannot be employed as a navigation mechanism for either CNs or BNNs. In terms of drug release, the collapse of nanobubbles at 298 K and 1 atm generates a high-energy water nanohammer, characterized by a temperature of approximately 1000 K and a pressure of 25 GPa, which impacts the nanocapsules. The impulse from the water nanohammer crushes the CN nanocapsule, whereas it leads to wall breakage in the BNN nanocapsule. Although both crushing and breakage can enable drug release, the crushing of CNs presents a higher risk of damage to the encapsulated drug. In summary, BNNs demonstrate better diffusivity and more favorable drug release behavior under nanobubble cavitation. However, further investigation is required to address targeting mechanisms and safer release strategies, involving the use of metallic functional groups and beam radiation, respectively. Full article