Search Results (125)

Biomass is one of the most important sources of renewable energy, generating large amounts of ash. This increases the amount of waste, landfill, and air pollution. This work focuses on the sustainable disposal of this ash by producing an innovative binder. The mechanical and microstructural properties of alkali-activated biomass fly ash (BFA) and diatomite (DT) mixtures are currently insufficiently studied. New scientific knowledge of these properties is needed. This study presents the possibility of using BFA and diatomite as aluminosilicate precursors for the production of an alkaline-activated binder. It was found that the reactivity of BFA is relatively low. Based on XRD analysis, the mineral composition of BFA is dominated by quartz and calcite, both of which are non-reactive minerals. Therefore, mixtures with DT were created as precursors. According to Rietveld analysis data, an amorphous part was found in both precursor materials, BFA and DT. Comparing the chemical composition of BFA and DT using XRF and Rietveld analysis data, it was found that the amorphous part of BFA consists of CaO, while the amorphous part of DT consists of SiO₂. Thus, the combination of these precursors should complement each other during the geopolymerisation process. After 28 days of curing, the strength of the binders was dependent on the amount of DT, and the highest strength values, such as 16.4 MPa and 15.3 MPa, were obtained when DT contents were 10% and 30%, respectively. After geopolymerisation, XRD analysis showed that calcium silicate hydrate, hydrotalcite, and calcium aluminium silicate hydrate (zeolite A type) were formed. SEM analysis confirmed the XRD results and showed that DT additives (10% and 30% by weight) improved the microstructure of alkali-activated BFA, which is closely related to compressive strength values. The proposed binder will be useful in the preparation of concrete, which could be used for artificial aggregates or small architectural elements. Full article

Factor VIII (FVIII) interacts with Endoplasmic Reticulum (ER) chaperones Calnexin (CANX) and Calreticulin (CALR) and with ER-Golgi Intermediate Compartment (ERGIC) transporters, Lectin, mannose-binding 1 (LMAN1) and Multiple Coagulation Deficiency 2 (MCFD2). We previously reported that the Gamma-aminobutyric Acid Receptor-associated proteins (GABARAPs) also influence FVIII secretion. Here, we further investigated the intracellular dynamics of FVIII using single and double CRISPR/Cas9 Knockout (KO) models of the abovementioned chaperones as well as the GABARAP proteins in HEK293 cells expressing FVIII. Cellular pathways were manipulated by Brefeldin A (BFA), Chloroquine (CQ), a Rab7 inhibitor, and subjected to glucose starvation. The effect of each KO on FVIII secretion and organelle distribution was assessed by a two-stage chromogenic assay and immunofluorescence (IF) microscopy, prior and upon cell treatments. Using these approaches, we first observed distinct effects of each studied protein on FVIII trafficking. Notably, intracellular localization patterns revealed clustering of FVIII phenotypes in GABARAP^KO, CANX^KO, and CALR^KO cells together under both basal and treated conditions, an observation that was also reflected in their respective double KO combinations. Besides, a clear involvement of additional components of the endomembrane system was evident, specifically at the trans-Golgi space, as marked by FVIII colocalization with the Ras-like proteins in brain (Rab8 and Rab7) and with the Vesicle-Associated Membrane Protein (VAMP8), along with the observed impact of the selected cell treatments on FVIII phenotypes. These outcomes enhance our understanding of the molecular mechanisms regulating FVIII and pave the way for new perspectives, which could be further projected into FVIII replacement, cell and gene therapies. Full article

Background/Objectives: University students are particularly susceptible to mental health issues, exhibiting a higher prevalence of insomnia and depressive symptoms compared to the general population. These mental problems adversely affect their academic performance and overall well-being. Understanding this issue is essential for developing effective prevention and intervention strategies for the academic community. The present study investigates the complex role of problematic TikTok use and insomnia in relation to depression among university students. Methods: An online cross-sectional survey was conducted between November 2024 and January 2025, involving a sample of 173 university students in Poland. The participants had a mean age of 23 years (M = 23.09, SD = 3.92), with 73.4% being women, and 49% were enrolled in medical and healthcare faculties. The questionnaire comprised a demographic survey, the Patient Health Questionnaire (PHQ-9) for assessing symptoms of depression, the Athens Insomnia Scale (AIS-8) for measuring symptoms of insomnia, and the modified Bergen Facebook Addiction Scale (BFAS) for evaluating problematic TikTok use (PTTU). The hypotheses were verified using Student’s t-test, Pearson’s correlation, and general linear model (GLM) mediation analysis. Results: The study found no significant gender (women vs. men) and faculty (medical vs. non-medical) differences in the level of symptoms of depression, insomnia, or problematic TikTok use. Insomnia, depression, and PTTU were positively inter-related. Insomnia completely mediates the relationship between PTTU and depression in university students. However, these results must be treated with caution due to the uneven gender distribution and cross-sectional nature of these studies, which limits causal relationships. Conclusions: Excessive engagement with TikTok has been associated with an increase in insomnia symptoms, which subsequently exacerbates depression symptoms among university students. Prevention and intervention strategies should prioritize reducing TikTok usage while simultaneously enhancing sleep hygiene and mental health within the academic population, irrespective of gender and university faculty affiliation. Full article

The bivariate fertilizer applicator (BAF) is a crucial device for precision agriculture, and the optimization of the control sequence optimization (CSO) significantly impacts the performance of variable-rate fertilization (VRF). This study investigates the CSO problem as a multi-objective optimization problem (CSO-MOP) for BFA through the lens of balanced trade-offs among conflicting objectives, including fertilization accuracy, uniformity, and adjustment rapidity. We employed three multi-objective evolutionary algorithms (MOEAs), including NSGA-III, MOEAD-D, and AR-MOEA. To investigate the problem, we solved several instances for different target fertilization rates and selected appropriate evaluation metrics. Finally, we obtained the Pareto set (PS) from each MOEA and conducted a comparative analysis, including the performance of each algorithm in addressing the CSO-MOP, the conflicts between each pair of objectives, and the effects of the optimized control sequences derived from each algorithm on the three objectives. Full article

Mycobacterium tuberculosis, the infectious agent behind tuberculosis (TB), underscores the significance of targeting enzymes such as arabinosyltransferases in drug development efforts. Benzothiozinone derivatives, which have been assessed for their effectiveness against TB, present a promising avenue for treatment. Utilizing a high virtual screening quantitative structure–activity relationship (QSAR-VS), a set of forty Benzothiozinone (C1–C40) compounds were investigated to build a robust model with satisfactory performance metrics (R² = 0.82, R²_adj = 0.78, N_test = 10, R²_test = 0.70). This model enabled the creation of databases containing new derivatives for screening drug-like properties and predicting MIC activity in TB treatment. The best-scoring compounds were screened by molecular docking with Mycobacterium tuberculosis kinases A and B (PDB code: 6B2P) and validated by molecular dynamics simulations to elucidate the most stable drug–protein interactions. Additionally, the MM-PBSA analysis shows that the strongest binding occurs in complexes X3, X4, and X6 with ΔG_bind values of −8.2, −15.3, and −12.0 kcal/mol, respectively. Our in silico study aims to prospect these new anti-tubercular drugs and their potential development through perspective in vitro and in vivo assays. Full article

To address the issues of poor environmental adaptability and high costs associated with traditional methods of measuring water body boundaries, this paper proposes an innovative path planning approach for water body boundary measurement based on Unmanned Surface Vehicles (USVs)—the Chemotactic Search Traversal (CST) algorithm. This method incorporates the chemotaxis operation mechanism of the Bacterial Foraging Optimization algorithm, integrating it with high-resolution grid maps to enable efficient traversal and accurate measurement of water body boundaries within large-scale grid environments. Simulation experiments demonstrate that the CST algorithm outperforms the Brute Force Algorithm (BFA), Roberts operator, Canny operator, Log operator, Prewitt operator, and Sobel operator in terms of optimal pathfinding, stability, and path smoothness. The feasibility and reliability of this algorithm in real water environments are validated through experiments conducted with actual USVs. These findings suggest that the CST algorithm not only enhances the accuracy and efficiency of water body boundary measurement but also offers a cost-effective and practical solution for measuring water body areas. Full article

Chlorella, recognized for its high lipid and protein content, is increasingly studied for its potential in the food and bio industries. To enhance its production and understand the underlying mechanisms of lipid accumulation, this study investigated the role of endoplasmic reticulum (ER) stress in modulating lipid metabolism in Chlorella sorokiniana UTEX 2714, using six putative ER stress inducers: 2-deoxy-D-glucose (2-DG), dithiothreitol (DTT), tunicamycin (TM), thapsigargin (TG), brefeldin A (BFA), and monensin (Mon). The results showed that 2-DG, DTT, TM, BFA, and Mon significantly inhibited cell growth in C. sorokiniana. Treatment with 2-DG, DTT, TM, BFA, or Mon resulted in substantial increases in the triacylglycerol (TAG) to total fatty acid (tFA) ratio, with fold changes of 14.8, 7.9, 6.2, 10.1, and 8.9, respectively. Among the tFAs, cells treated with these compounds exhibited higher levels of saturated fatty acids and lower levels of polyunsaturated fatty acids (PUFAs). In contrast, the fatty acid composition of TAGs showed the opposite trend, with relative enrichment in PUFAs. This study enhances our understanding of Chlorella lipid metabolism, providing valuable insights for optimizing lipid production, particularly TAGs enriched with PUFA content, for applications in functional foods, nutraceuticals, and sustainable bioresources. Full article

This study examines four shallow-water, reef-coral-bearing carbonate successions belonging to the Jhill Limestone Unit of the Gaj Formation, exposed in the area near Karachi (southern Pakistan). Sixty-two samples were collected for the quantitative analysis of the skeletal and foraminiferal assemblages. The analysis of large benthic foraminifera suggests a placement within the late Oligocene, characterized by the setup of the Late Oligocene Warming Event. Thanks to quantitative analyses and multivariate statistics, three biofacies were identified: (1) the reef coral biofacies (BFA), indicative of a sheltered, shallow-water environment above fair-weather wave base; (2) the coralline algal biofacies (BFB), deposited within a mesophotic setting and representing the deepest biofacies among the three recognized ones; and (3) the large benthic foraminiferal and coralline algal biofacies (BFC), subdivided into two sub-biofacies, namely (a) the miogypsinid, thin and flat large benthic foraminiferal and coralline algal sub-biofacies (BFC1), indicative of deeper setting, comprised between BFA and BFB, and (b) the miogypsinid and coralline algal sub-biofacies (BFC2), indicative of shallower settings than BFC1, and bearing evidence of paleo-seagrass meadows. All these biofacies were developed within the photic zone, in a relatively flat seafloor punctuated by patch reefs and seagrass meadows and characterized by a notable nutrient influx. Foraminiferal-based experimental paleobathymetric parameters, including the lepidocyclinids/miogypsinids, the flat nummulitids/lepidocyclinids, and the hyaline/porcelaneous foraminifera ratios, were tested and confirmed as reliable tools for paleodepth and paleoenvironmental reconstructions. Full article

The integration of deep learning and remote sensing for the rapid detection of landslides from high-resolution remote sensing imagery plays a crucial role in post-disaster emergency response. However, the availability of publicly accessible deep learning datasets specifically for landslide detection remains limited, posing challenges for researchers in meeting task requirements. To address this issue, this study develops and releases a deep learning landslide dataset using Google Earth imagery, focusing on the impact zones of the 2008 Wenchuan Ms8.0 earthquake, the 2014 Ludian Ms6.5 earthquake, and the 2017 Jiuzhaigou Ms7.0 earthquake as the research areas. The dataset contains 2727 samples with a spatial resolution of 1.06 m. To enhance landslide recognition, a lightweight boundary-focused attention (BFA) mechanism designed using the Canny operator is adopted. This mechanism improves the model’s ability to emphasize landslide edge features and is integrated with the ResUNet model, forming the ResUNet–BFA architecture for landslide identification. The experimental results indicate that the ResUNet–BFA model outperforms widely used algorithms in extracting landslide boundaries and details, resulting in fewer misclassifications and omissions. Additionally, compared with conventional attention mechanisms, the BFA achieves superior performance, producing recognition results that more closely align with actual labels. Full article

In jointless bridges, a grade flat approach slab (GFAS) with the same elevation as the pavement can transfer the girder’s longitudinal deformation to the backfill. However, any cracks and settlement of the pavement usually occur at the end of the GFAS. To address this shortcoming, the buried flat approach slab (BFAS) horizontally embedded at a depth in the backfill was proposed. The complicated flat approach slab–soil interaction (FASSI) of the BFAS has not been systemically investigated. To address this gap, the influence of the FASSI on the mechanical performance of the approach slab and the backfill deformation was investigated in this research to understand the mechanism of the FASSI in absorbing one part of the girder’s longitudinal deformation and transferring the rest to the soil. Experimental tests on the FASSI with different embedded depths under longitudinal displacements were conducted. Numerical parametric analyses were carried out by considering the embedded depths and slab lengths as the parameters based on a finite element model verified using the test results. The results show that load–displacement curves of the FASSI comprise three stages: the elastic stage (approach slab’s displacement was absorbed by sand), the elastoplastic stage (sand deformation was observed), and the failure stage (overall shear failure of the sand was found). The longitudinal displacement transfer mode and vertical deformation distribution mode of the sand were affected by the embedded depth and slab length. With an increase in the embedded depth or a decrease in the slab length, the sand deformation decreases, which is beneficial for avoiding pavement crack risks and improving the pavement evenness. Finally, a simplified calculation formula that can be used to predict the load–displacement curves of the FASSI was proposed. This research provides the theoretical basis for the design and construction of the flat approach slab in jointless bridges. Full article

Stress on the Endoplasmic reticulum (ER) can severely disrupt cellular function by impairing protein folding and post-translational modifications, thereby leading to the accumulation of poor-quality proteins. However, research on its impact on photosynthesis remains limited. In this study, we investigated the impact of ER stress on the photosynthetic efficiency of Chlamydomonas reinhardtii using pharmacological inducers, tunicamycin (TM) and brefeldin A (BFA), which specifically target the ER. Our measurements of photosynthetic parameters showed that these ER stress-inducing compounds caused a significant decline in photosynthetic efficiency. A proteomic analysis confirmed that TM and BFA effectively induce ER stress, as evidenced by the upregulation of ER stress-related proteins. Furthermore, we observed a widespread downregulation of photosynthesis-related proteins, which is consistent with the results obtained from our measurements of photosynthetic parameters. These findings suggest that the stress on ER has a profound impact on chloroplast function, disrupting photosynthetic processes. This study highlights the critical interdependence between the ER and chloroplasts, and it underscores the broader implications of ER stress on the cellular metabolism and energy efficiency of photosynthetic organisms. Full article

This research introduces a hybrid approach combining bio- and nature-inspired metaheuristic algorithms to enhance scheduling efficiency and minimize energy consumption in Underwater Acoustic Sensor Networks (UASNs). Five hybridized algorithms are designed to efficiently schedule nodes, reducing energy costs compared to existing methods, and addressing the challenge of unscheduled nodes within the communication network. The hybridization techniques such as Elephant Herding Optimization (EHO) with Genetic Algorithm (GA), Firefly Algorithm (FA), Levy Firefly Algorithm (LFA), Bacterial Foraging Algorithm (BFA), and Binary Particle Swarm Optimization (BPSO) are used for optimization. To implement these optimization techniques, the Scheduled Routing Algorithm for Localization (SRAL) is introduced, aiming to enhance node scheduling and localization. This framework is crucial for improving data delivery, optimizing Route REQuest (RREQ) and Routing Overhead (RO), while minimizing Average End-to-End (AE2E) delays and localization errors. The challenges of node localization, RREQ reconstruction at the beacon level, and increased RO, along with End-to-End delays and unreliable data forwarding, have a significant impact on overall communication in underwater environments. The proposed framework, along with the hybridized metaheuristic algorithms, show great potential in improving node localization, optimizing scheduling, reducing energy costs, and enhancing reliable data delivery in the Internet of Underwater Things (IoUT)-based network. Full article

To address SDG12 (ensure sustainable consumption and production patterns), and to provide technical evidence for alternative concrete constituents to traditional natural river sand, stone fine aggregate (SFA), brick fine aggregate (BFA), ladle-refined furnace slag aggregate (LFS), recycled brick fine aggregate (RBFA), and washed waste fine aggregate (WWF), ready-mix concrete plants were investigated. Concrete and mortar specimens were made with different variables, such as replacement volume of natural sand with different alternative fine aggregates, water-to-cement ratio (W/C), and sand-to-aggregate volume ratio (s/a). The concrete and mortar specimens were tested for workability, compressive strength, tensile strength, and Young’s modulus (for concrete) at 7, 28, and 90 days. The experimental results show that the compressive strength of concrete increases when natural sand is replaced with BFA, SFA, and LFS. The optimum replacement amounts are 30%, 30%, and 20% for BFA, SFA, and LFS, respectively. For RBFA, the compressive strength of concrete is increased even at 100% replacement of natural sand by RBFA. For WWF, the compressive strength of concrete increases up to a replacement of 20%. Utilizing these alternative fine aggregates can be utilized to ensure a circular economy in construction industries and reduce the consumption of around 30% of natural river sand. Full article

Poplars are crucial for timber supply and ecological protection in China. Enhancing the growth of poplar plantations and improving soil fertility in arid, and semi-arid poor soil regions are key aspects of sustainable forest management. Fertilization (FTL) and drip irrigation (DI) are among the most widely used methods globally for increasing yield and soil productivity. This study conducted field experiments on FTL and DI in a 10-year-old Populus × canadensis ‘Zhongliao 1’ (cultivation varieties of P. canadensis in northern China) plantation. DI limits were set according to soil moisture at 60% (S1), 70% (S2), and 80% (S3) of field capacity; nitrogen FTL rates were set at 100% of the baseline fertilization amount (100% BFA, N 643.20 g·year⁻¹, P 473.37 g·year⁻¹, and K 492.29 g·year⁻¹) (F1), 70% BFA (F2), 130% BFA (F3), and 160% BFA (F4). The treatments of drip irrigation and fertigation (DIF) were H1 (100% BFA, 60% FC), H2 (100% BFA, 80% FC), H3 (160% BFA, 60% FC), and H4 (160% BFA, 80% FC), along with a control group (CK) without any management, totaling 12 experimental combinations. The results showed that the H4 had the most significant promoting effect on the height, DBH, and volume increments. All treatments had little effect on the soil bulk density of the plantation but significantly impacted soil capillary porosity and pH. Compared to DI, soil nutrient and organic matter content were more sensitive to FTL. Appropriate FTL and DI can increase soil sucrase activity. Soil urease activity tended to increase with higher FTL rates, and higher DI levels also positively influenced urease activity. Excessive or insufficient soil moisture and nutrients negatively impacted soil cellulase and catalase activities. Correlation analysis revealed no significant correlation between the growth of P. × canadensis ‘Zhongliao 1’ and soil nutrient content, but significant or highly significant correlations existed between growth and soil porosity and related enzyme activities. Comprehensive evaluation using a membership function indicated that high FTL levels (F4) were more conducive to the simultaneous improvement of the growth and soil fertility of the plantation, followed by H4 and F1, suggesting that high FTL is the key factor affecting the growth of 10-year-old P. × canadensis ‘Zhongliao 1’ plantations and the restoration of stand productivity, with moisture being secondary. Full article

In the process of using multi-channel ground-penetrating radar (GPR) for underground cavity exploration, the acquired 3D data include reflection data from underground cavities or various underground objects (structures). Reflection data from unspecified structures can interfere with the identification process of underground cavities. This study aims to identify underground cavities using a C-GAN model with an applied ResBlock technique. This deep learning model demonstrates excellent performance in the image domain and can automatically classify the presence of cavities by analyzing 3D GPR data, including reflection waveforms (A-scan), cross-sectional views (B-scan), and plan views (C-scan) measured from the ground under roads. To maximize the performance of the C-GAN model, a background filtering algorithm (BFA) was developed and applied to enhance the visibility and clarity of underground cavities. To verify the performance of the developed BFA, 3D data collected from roads in Seoul, Republic of Korea, using 3D GPR equipment were transformed, and the C-GAN model was applied. As a result, it was confirmed that the recall, an indicator of cavity prediction, improved by approximately 1.15 times compared to when the BFA was not applied. This signifies the verification of the effectiveness of the BFA. This study developed a special algorithm to distinguish underground cavities. This means that in the future, not only the advancement of separate equipment and systems but also the development of specific algorithms can contribute to the cavity exploration process. Full article