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Strength-energy-damage analysis of additional silica fume-fiber synergistically reinforced shotcrete
No full textAs mining operations extend deeper underground, the extraction of mineral resources faces increasingly extreme conditions. The immense in-situ stresses, violent rock bursts triggered by excavation, and intricate groundwater systems at such depths place unprecedented demands on strength and durability of shotcrete used for primary roadway support. This study investigates silica fume (SF) hybrid fiber-reinforced shotcrete (SFHF-S), focusing on joint effects of polypropylene fiber (PPF), SF, and steel fiber (STF) on its characteristic behavior after 14 days of curing. Strength, energy dissipation, damage evolution, and microstructural features of SFHF-S were explored by uniaxial compression, splitting tensile, and SEM-EDS analyses. Results show that STF had the most pronounced influence on mechanical strength enhancement. Specimens with 1.5 vol% STF exhibited high toughness, while the hybrid fiber system markedly improved uniaxial compressive strength (UCS), with SF acting as a supplementary modifier. At 0.2 vol% PPF, 1.5 vol% STF, and 10 wt% SF, UCS and splitting tensile strength (STS) augmented by 3.4 MPa and 0.38 MPa, respectively. SF improved matrix compactness and stiffness, significantly increasing the elastic modulus and reducing peak strain. The hybrid system produced a greater modulus increase than single-fiber shotcrete, demonstrating strong synergy. SFHF-S system inhibited rapid crack propagation through a “stepwise crack inhibition and continuous energy dissipation” mechanism, leading to complex failure modes characterized by interwoven tensile and shear cracks and narrower primary cracks. Increasing the SF content reduced pore depth, width, and connectivity within the matrix. Overall, SFHF-S exhibits superior mechanical performance and durability under high-stress conditions, enhancing the load-bearing capacity and stability of roadway support structures in deep mining environments
Clustering: Cluster Evaluation
No full textData Mining Dersi 14. Hafta Ders Notu Konusu : Clustering: Cluster Evaluatio
Physiological and growth responses of black sea salmon (salmo labrax) to long-term salinity and high carbon dioxide stress
No full textBlack Sea salmon (Salmo labrax), an anadromous salmonid species of regional importance, is increasingly considered for aquaculture in the Black Sea. This study investigates the physiological and growth responses of Black Sea salmon to seawater transfer, with a particular focus on carbon dioxide (CO₂) stress. The experiment began on 5 July 2022 with 720 fish (76.68±15.34 g) reared under semi-controlled conditions using a freshwater recirculating aquaculture system (RAS). On 12 October 2022, a group of fish was transferred to Black Sea water (18 ppt), and a subgroup was exposed to elevated CO₂ (1000 µatm pCO₂) until the end of the trial on 7 March 2023. Exposure to carbon dioxide showed negligible or minimal effects on seawater adaptation and growth. In contrast, physiological markers such as gill Na⁺/K⁺-ATPase (NKA) activity and the expression of nkaα1a, nkaα1b, and nkcc1a genes, along with growth metrics—including specific growth rate (SGR), condition factor (K value), and liver gene expression of igf-I, igfbp1b, ghr1, and ctsl—indicated that the fish were not physiologically prepared for seawater transfer in autumn. These findings suggest that the commonly practiced autumn sea transfer in the region may lead to suppressed growth and suboptimal performance. The results emphasize the importance of aligning seawater transfer with the smoltification window to support fish health and optimize aquaculture outcomes in Black Sea salmon farming
Meta-analysis of effectiveness of pedagogical innovations involving technology in organic chemistry education in developing students’ academic performance
No full textBecause organic chemistry asks students to use visual and spatial thinking skills (e.g., three-dimensional structures of molecules) and comprehend various chemical reactions and mechanisms, it naturally needs pedagogical innovations involving technology to result in better academic performance. However, none of the previous studies has investigated the extent to which these pedagogical innovations are effective in improving students’ academic performance of organic chemistry education. This study aims to meta-analytically assess the effectiveness of the pedagogical innovations involving technology in organic chemistry education in developing students’ academic performance. The current meta-analysis handled 26 studies as the corpus of the data retrieved from the database and manual search. The authors initially coded the studies via a template form and inserted all statistical data from a Microsoft Excel sheet into Comprehensive Meta-Analysis (CMA V2) statistics software to calculate Hedges’ g for the corpus data. The findings pointed to the large effect for the overall effect size (g = 0.973). Also, it was found that only subgroups for the use of technological tools within the moderator variable “type of pedagogical innovations involving technology” played a significant role at predicting the students’ academic performance as a result of the treatments. In light of the findings, it can be inferred that the pedagogical innovations involving technology in organic chemistry education are more effective and fruitful in developing the students’ academic performance than nontechnology-based control groups. Further, the current meta-analysis study concludes that high school (for educational level), flipped classroom (for the pedagogical models including technology), digital media (for the use of technological tools), and short-term treatment (for implementation duration) act as the most effective variables to learn organic chemistry via the pedagogical innovations. Future research should focus on other individual and moderator variables to offer more adaptive alternatives for the use of chemistry teachers and lecturers
Energy security, institutional quality, and geopolitical risks: evidence from türkiye and sub-saharan africa countries
No full textThis study examines the effects of energy security, institutional quality, and geopolitical risks on oil price uncertainty in the context of Türkiye and Sub-Saharan African countries. The literature emphasises that energy security is critical for sustainable economic growth and is directly affected by geopolitical tensions and weak institutional structures. Empirical findings show that energy security and geopolitical risks increase oil price uncertainty, inflation fuels uncertainty, and consumption increases play a mitigating role. Furthermore, political stability is a strong determinant of volatility. Descriptive statistics and correlation analysis show a negative relationship between energy security and oil price uncertainty, and a positive relationship between energy security and geopolitical risks. The results reveal that strengthening institutional capacity, diversifying energy sources, and enhancing international cooperation are critical for energy security and macroeconomic stability
Identification and development of pathogen- and pest-specific defense–resistance-associated ssr marker candidates assisted by machine learning and discovery of putative QTL hotspots in camellia sinensis
No full textIn this study, a targeted SSR (Simple Sequence Repeat) marker resource was developed based on genes and protein families associated with pathogen- and pest-related defense–resistance mechanisms in Camellia sinensis. Forty-one genes and protein families reported to show upregulation, increased expression, or functional validation under disease and pest stress were selected, and the corresponding 195 loci were mapped onto the Camellia sinensis cv. Shuchazao genome. SSR screening within gene bodies and gene-flanking regions (±5 kb) identified 5197 SSR loci. Putative QTL hotspot regions were defined using locus-based sliding-window analysis, Z-score calculations, and permutation tests, yielding 633 SSRs filtered at the 99% and 95% significance thresholds. Proteome-wide scans based on conserved amino acid motifs identified multiple loci within the WRKY, NAC, LRR, PRX, and CHI families, and Random Forest analysis was used to prioritize SSRs within these families. Finally, 386 SSR primer sets were designed and evaluated by in silico PCR across six tea genomes. Of these, 245 primers produced amplicons in more than one genome, and 124 exhibited polymorphic information content values greater than 0.500. Overall, the developed SSR panels represent a biologically contextualized and experimentally transferable marker resource targeting defense–resistance-associated genic and gene-proximal regions
Biomechanical analysis of soft tissue thickness in residual limb: impact on stress distribution and interface pressure in prosthetic fitting
No full textThe thickness of the residual limb’s soft tissue plays a crucial role in determining the mechanical behavior and stress distribution at the stump–prosthesis interface. Using finite element analysis (FEA), this study investigates the biomechanical effects of different soft tissue thicknesses (30 mm, 50 mm, and 70 mm) on stress distribution. A patient-specific finite element model of the residual limb was developed to simulate realistic anatomical and mechanical conditions. To replicate physiological loading, a static vertical load of 350 N was applied, and the interface between the residual limb and the prosthetic liner was modeled using appropriate contact mechanics. The results revealed that reducing the soft tissue thickness to 3 cm produced higher Von Mises stress concentrations (0.115 MPa) and contact pressure (0.0697 MPa), which may increase discomfort and the risk of tissue damage. Conversely, increasing the thickness to 70 mm reduced stress values (0.016 MPa) and contact pressure (0.0312 MPa) but led to excessive deformations (6.277 mm) that could compromise prosthetic stability. An optimal soft tissue thickness of 5 cm was identified, where Von Mises stress and contact pressure remained at moderate levels, offering a balance between stress distribution and mechanical stability. These findings provide valuable guidance for optimizing prosthetic socket design, as maintaining appropriate soft tissue thickness can enhance comfort, reduce pressure-related injuries, and improve the overall functionality of lower-limb prostheses
A novel passive cooling configuration for photovoltaic panels based on bio-inspired heatsinks and nanoparticle-enhanced PCM
No full textThis study presents the design, fabrication, and experimental evaluation of a novel passive thermal management system for photovoltaic (PV) modules that integrates a bio-inspired aluminium heatsink with a nanoparticle-doped phase change material (PCM). The proposed configuration aims to regulate the temperature of the PV module under real outdoor conditions without any external energy input. The bio-inspired heatsink was designed based on coral-like branching geometry to enhance natural convection and heat distribution within the PCM. The PCM, doped with metal-oxide nanoparticles (Al2O3, SiO2, TiO2) at a 2% mass fraction, provided additional latent-heat storage capacity and improved thermal conductivity. Experimental tests were conducted using two identical monocrystalline PV panels. The results demonstrated that the bio-inspired-cooled PV module effectively reduced surface temperature fluctuations by 8–15 °C and achieved a maximum efficiency improvement of 9.2% compared to the uncooled configuration. The integration of the PCM layer with the bio-inspired heatsink maintained a more stable operating temperature throughout the day, particularly during high-irradiance conditions. Hourly I-V and P-V analyses confirmed that the hybrid module consistently exhibited higher maximum power and efficiency values. Furthermore, the estimated energy yield analysis revealed that the average efficiency gain of 5.6% achieved under outdoor conditions could lead to a substantial increase in annual energy production. Overall, the hybrid bio-inspired fins + PCM system offers a sustainable, self-regulating, and energy-free cooling solution that enhances both the performance and durability of PV modules
Evaluation of rainbow trout response to the optimal anesthetic concentration of citronella oil (Cymbopogon nardus) predicted by artificial neural network
No full textAnesthesia practices in aquaculture are important for preventing potential stress in fish. For this purpose, interest in natural anesthetic agents as substitute for currently used synthetic anesthetics has increased. In this context, the present study demonstrated the anesthetic efficacy of citronella oil (Cymbopogon nardus) in rainbow trout (Oncorhynchus mykiss) individuals. Based on an artificial neural network (ANN) model derived from preliminary studies, the optimal anesthetic concentration for rainbow trout individuals was estimated as 90 μL L−1. Validation of the concentration predicted by ANN revealed no time-dependent hematological or histological effects on fish to citronella oil. Furthermore, biochemical tests revealed that the partial post-anesthesia increase in ALT and AST values was transient and negligible in light of histological findings. Although oxidative stress was observed during the acute period, the enzymatic activity of SOD and CAT effectively reduced the oxidative damage, demonstrating their role in protecting the fish from oxidative stress. The antioxidant activity observed was temporary, returning to baseline levels without any accompanying tissue damage at the tested concentration. Behavioral monitoring further indicated a swift reduction in motor activity followed by a smooth recovery process, with no evident signs of stress or avoidance behaviour. Overall, these results position citronella oil as a promising natural anesthetic for rainbow trout under the studied parameters. That said, further studies involving various solvents, temperature ranges, and fish species are necessary to comprehensively establish its efficacy and safety