As multi-core processors scale to tens or hundreds of cores, efficiently mapping dynamic application workloads becomes critical to avoid thermal hotspots, energy waste, and deadline violations. Conventional static or heuristic mapping schemes fall short under run-time variability in task sizes, thermal coupling, and load imbalance. In this paper, a Reinforcement Learning–Driven Task-to-Core Mapping framework that jointly optimizes temperature, energy, performance, and load balance in a closed-loop simulation environment using ARM based multicore architecture is presented. The model is mapped as a state space model: each decision state encodes per-core load and temperature along with the next task’s profiled features; actions assign the task to one of N cores; and a multi-objective reward, dynamically weighted by task criticality and sensitivity parameters, guides learning via Q-learning. To ensure timeliness, the mapping is followed with a novel urgency-score scheduler that recalculates each task’s WCET and deadline based on run-time load and temperature and combines deadline urgency with starvation balancing. Evaluated on MiBench-derived workloads, our approach reduces makespan by up to 13%, saves ~6% energy, lowers peak temperature by ~5.95%, achieves sub-1% deadline miss-rate and delivers smallest jitter—outperforming task assignment and scheduling baselines.
An optimized gas sensor that operates at room temperature is highly suitable for industrial safety applications. Polyvinyl alcohol (PVA) was embedded with gold nanoparticles (Au NPs) to produce the ammonia (NH3) gas sensor. These films were synthesized successfully using two different stages: (1) pulsed laser ablation in liquid method to prepare Au nanoparticles, and (2) solvent casting method to embed nanoparticles into PVA substrates. The gas detection capability of the films was investigated based on their optical, morphological, structural, crystallographic, and dielectric features. Field emission scanning electron microscopy confirmed nanoscale and well-dispersed Au NPs within the PVA substrate. X-ray diffraction analysis showed crystallinity improvement from 44.91% (pure PVA) to 76.41%. UV-visible spectroscopy confirmed the slight decrease in the optical bandgap from 4.89 eV to 4.27 eV. The dielectric measurements exhibit enhanced electrical conductivity of PVA embedded with 3% of Au nanoparticles, which is directly correlated with the improvement of gas sensing capability. The sensor exhibited an effective response of around 64.2% and had a sensitivity of 1.62 with a response time of 6s at room temperature under a 600 ppm NH3 gas concentration. That showed a greater sensitivity compared to pure PVA film.
The present study was conducted during the spring of 2024 to investigate the distribution and speciation of iron in main soil orders from various locations in the Erbil Governorate. The analysis was carried out using a sequential extraction procedure to fractionate iron into operationally defined forms: Exchangeable Fe, Carbonate Fe, Organic bound Fe, Reducible Fe, Residual Fe, Soluble Fe, Available Fe and Total Fe. Soils representing four main soil orders which included Inceptisols, Mollisols, Vertisols and Aridisols were collected from various sites including Mergasur, Choman, Shaqlawa, Rawanduz, Koya, Daraban, Harir, Grdarasha, Omermamk, Dibaga, Makhmour, and Qaraj. The results revealed significant variability in iron fractions among the locations. The residual iron form was dominant across all samples, with the highest value observed in Qaraj (85.53 mg kg-1) and the lowest in Omermamk (62.85 (mg kg-1). Exchangeable and available iron were remarkably high in Omermamk (61.00 mg kg-1 and 63.08 mg kg-1 respectively), suggesting unique geochemical conditions at that site. In contrast, most other soils contained exchangeable iron below (5 mg kg-1). Soluble iron remained generally low across the study area, with the highest value detected in Koya (5.02 mg kg-1). Overall, the findings indicate that while residual forms of iron dominate, certain areas like Omermamk exhibit unusually high levels of exchangeable iron, potentially enhancing plant iron uptake. These results contribute to a better understanding of iron dynamics in Erbil soils and support the development of site-specific soil fertility management strategies.
The relationship between dietary mineral supplementation and sex preselection in livestock animals was not fully understood. Conflict results have been shown from difference methods of applying to supplement minerals by earlier studies. Hence, in this study, sheep fed diets supplemented with dietary Ca (Calcium) and Mg (Magnesium) via feeding route to examine sex ratios skewing toward female. Thirty Kurdish breed ewes were divided into two groups; control and CaMg (15 ewes per each group). Control group ewes offered a diet (1 kg concentrate with ad libitum wheat straw). While, ewes in CaMg group fed diet supplemented with Ca and Mg. Diets were offered twice a day (in the morning and evening) over a period of one-month. There was no effect (P>0.05) of dietary supplementation of CaMg on final live weigh of ewes. Although, ewes at CaMg had numerically (1.7 kg on average) lower live body weight than control. Similarly, serum (glucose, Ca, Mg, estrogen, and progesterone) were not difference (P>0.05) among control and CaMg group. In addition, the ratio of male and female new born lambs were not affected by CaMg supplementation (P>0.05). Although, in controls, female offsprings (47%) were which was 6% fewer than males (53%), whereas CaMg supplementation increased the proportion of females from 39% in control to 61% (+14 percentage). This represents a shift in sex bias of +28 percentage, from 6% fewer females to 22% more. Results of this study suggested a potential of skewing sex ratio towards female through dietary supplementation of Ca and Mg.
One of the most frequent types of asphalt pavement failure is rutting. Pavement failures can be greatly reduced or delayed by improving asphalt binder’s characteristics. High-performance pavements require high-quality asphalt that contains composite modifiers. In this study, a combination of polymer and nanoparticles was used to modify a local 40/50 penetration-grade asphalt binder (PG 70-16). Fixed dosages of carbon nanotubes (CNTs), nano silica (NS), styrene-butadiene-styrene (in both granular (SBSG) and powdered (SBSP) forms) were applied individually and in hybrid combinations. A series of physical, rheological tests, field emission scanning electron microscopy (FESEM) and energy-dispersive spectroscopy (EDS) were used to examine unmodified and modified asphalt binders to evaluate improvements in key performance characteristics. As well as, the comparison of the effectiveness of SBSG and SBSP in asphalt binder modification. According to the results, the additions improved viscosity, raised the softening point, penetration index, and flash point, while penetration decreased. High-temperature improvements were validated by DSR results. While BBR showed changes in low-temperature grades. The improvements were attained by increasing high temperature grade as follows: 4% SBS raised the grade to PG 76-16, while CNTs and hybrid of nanomaterials increased it to PG 82-16, NS alone gave PG 70-16. PG 88-10 was attained by the triple hybrid of polymer with nanomaterials. FESEM results revealed improved compatibility and dispersion, particularly in composite modified asphalt binders of (SBSP + NS + CNTs). SBSP outperformed SBSG in most of the tests, enhancing rutting resistance, penetration, softening point, and fatigue performance due to its stronger elastic polymer network.
This paper introduces a compact convolutional neural network (CNN) architecture integrated with a multi-head attention mechanism to enhance feature discrimination in malware family classification. The novelty lies in combining attention-based refinement within a lightweight framework that achieves comparable accuracy to larger model while maintaining computational efficiency. The integrated multi-head attention module emphasizes small yet highly discriminative regions, which often correspond to obfuscated or subtly modified code segments that traditional models overlook. In contrast to reverse engineering or handcrafted feature methods, the framework is fully automated and computationally efficient, requiring only 2.03 M parameters approximately one-fifth of the baseline CNN while reducing training time by 42% and inference latency by 37% on the same hardware configuration. Experiments were conducted on the widely used Malimg dataset, which comprises 9,342 grayscale images across 25 malware families, under multiple train–test splits (50/50 to 90/10). The results consistently demonstrate superior performance relative to the baseline CNN, the model achieving an average accuracy of 98.7 ± 0.3% across five randomized train–test splits, with a peak performance of 99% on the 80/20 partition. Data partitions were strictly disjoint to prevent leakage between training and test sets. Furthermore, the proposed model attains high weighted Precision, Recall, and F1 scores (≈0.99) and enhanced macro-averaged performance (up to 0.97), particularly enhancing classification for minority families that the baseline misclassified or failed to detect. Confusion matrix analysis further highlights that residual misclassifications occur primarily in families with limited samples or high morphological similarity. Comparative evaluation against recent studies confirms the superiority of the proposed approach in terms of both accuracy and computational efficiency. Despite these strengths, limitations remain, including dependence on labeled datasets, restricted interpretability, and the need for validation on more diverse, real-world malware corpora.
The impacts of prolonged wars extend beyond physical destruction, affecting social fabric, urban identity, and infrastructure, while causing psychological and material harm to communities. Beirut is a unique case among Arab cities, having experienced multiple cycles of war and reconstruction that shaped its urban and social development. This study aims to reassess post-war reconstruction strategies through a comparative analysis of two initiatives: central Beirut after the civil war and the southern suburb after the 2006 war. The study focuses on how selecting the right strategy influences reconstruction success, including meeting community needs, preserving identity, and enabling participatory decision-making. The research assumes that success or failure in post-war urban reconstruction can be assessed through social, economic, political, cultural, and urban indicators. These include residents’ return, social integration, urban identity preservation, and infrastructure recovery. It also addresses a key problem: the limited local knowledge of how strategic choices affect the balance between physical recovery, community needs, and identity renewal. Findings show that both improved infrastructure, differences in governance, urban strategy, and priorities significantly shaped their social outcomes, identity preservation, and spatial integration. These outcomes reveal the influence of political and economic agendas—resistance narratives in the southern suburb versus market-driven priorities in central Beirut. Using Beirut as a case study, this research contributes to understanding how post-war reconstruction strategies in Arab cities can balance physical recovery with community needs and identity renewal.
Streptomyces isolates are particularly well known for producing enormous amounts of bioactive secondary metabolites, among which some exhibit exceptional antimicrobial activity. Twenty five Streptomyces isolates were isolated from tomato field soil and tested for their ability to inhibit Alternaria solani. Two such isolates, M1 (Streptomyces gilvosporeus), which inhibited A. solani 64%, and M5 (Streptomyces sp.), ineffective, were chosen. Secondary metabolites of these isolates were isolated and contrasted by Gas Chromatography-Mass Spectrometry (GC-MS), identifying 40 compounds in isolate M1 and 91 compounds in isolate M5. Among them, 12 bioactive compounds were found in common in both isolates. In the M1 extract, the most dominant detected constituents were 2-[2-(7-Chloro-7-norcaranyl)ethynyl]thiophene (4.88%), n-Hexadecanoic acid (6.88%), Methoxymethyl(triethyl)stannane (23.72%), Ergoline-8-carboxamide, 9,10-didehydro-N,6-dimethyl-, (8.beta.)- (8.68%), 1,2,6b,7,8,9,10,10a-Octahydroindeno[1,2,3,-cd]pyrene (15.91%). A second follow-up pot experiment confirmed that the M1 isolate and its secondary metabolites completely suppressed disease manifestation (100% suppression of early blight disease) and improved tomato plant growth significantly. This study illustrates the potential use of Streptomyces sp., particularly S. gilvosporeus, as superior and environmentally safe biocontrol molecules for the regulation of tomato early blight under agricultural settings.
Nanomaterials and their applications hold a promise for widespread use in agriculture, medicine, and industry. This research article explores the synthesis of some new 1,2-thiazine derivatives, highlighting their potential as antibacterial agents. In this work, a key innovation in this work is the development of a cost-effective, sustainable and environmentally friendly method for creating copper nanoparticles. These nanoparticles were synthesized using a green chemistry approach with an extract from Ziziphus mauritiana fruit, and were successfully used to improve the efficiency of the Ullmann coupling reaction. In the synthesized copper nanoparticles, enhancing of Ullmann coupling was shown to significantly improve in the synthesis of 1,2-thiazine derivatives. Furthermore, the study further investigated the oxidation of methyl groups on the thiazine ring. This oxidation led to convert of methyl group into aldehyde group. Several of the synthesized compounds demonstrated significant antibacterial activity against both Gram-positive bacteria, specifically Staphylococcus aureus, and Gram-negative bacteria, such as Escherichia coli. These findings suggest that copper nanoparticles could serve as a promising foundation for developing new antibacterial agents, potentially offering an effective and more natural alternative to conventional antimicrobial treatments. Moreover, this research provides a scientific pathway for the use of these compounds and nanoparticles in the pharmaceutical industry for the development of new drugs.
This study aims to synthesize an octahedral cobalt (II) complex coordinated with saccharin and water ligands. The resulting complex, [Co(sac)₂(H₂O)₄].H₂O, was obtained by reacting one equivalent of CoCl₂·6H₂O with two equivalents of sodium saccharin (Nasac) in a mixed ethanol-water solvent. The complex was characterized using FT-IR, single-crystal X-ray diffraction analysis, electronic spectroscopy, molar conductivity measurement, and theoretical studies, including noncovalent interactions, density functional theory (DFT), natural bond orbital (NBO) analysis, and surface analysis (MEP and Hirshfeld analysis). Characterization data and crystal structure analysis confirmed that the cobalt (II) center was coordinated to two saccharin nitrogen atoms and four water oxygen atoms in an octahedral geometry, with an additional water molecule positioned outside the coordination sphere. Molar conductivity measurements indicated that the complex behaves as a non-electrolyte in solution. The antibacterial activity of Nasac (sodium saccharin) and its cobalt complex was assessed against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli using the agar diffusion method. The results indicated that both Nasac and the Co(II) complex exhibit good antibacterial activity against the tested bacteria. Theoretical studies such as noncovalent interaction displayed (O3…O2W, O2W‒H2W1…O1, O1‒WH1w1…O2), (O1W‒H1WA…O2, O2…O2) and (π…π [C3…C6 & C2…C4]) interactions. It suggests that all the contacts are purely noncovalent. According to density functional theory (DFT), the Co(II) complex is less reactive and more stable than the Nasac ligand. A significant transfer of charge density from the saccharin ligand to the cobalt ion was shown by neutral bond orbital (NBO) studies. According to Hirshfeld surface analysis (HAS), the near H...O/O...H contacts account for 42.0 % of the total primary intermolecular interactions in the cobalt complex, which is the largest contribution.
Aguamiel, the fresh sap of Agave, holds cultural and nutritional relevance and has been increasingly studied as a functional prebiotic ingredient with documented effects on gut microbiota modulation. This study aimed to evaluate the bibliometric landscape of scientific research on aguamiel and Agave-derived fructans by retrieving original articles from the Web of Science Core Collection (2006–2024) using a structured Boolean query and analyzing the dataset with R bibliometrix and VOSviewer to interpret research trends, technological approaches, and health-related implications. Data were processed to generate descriptive indicators, co-authorship and keyword co-occurrence networks, temporal evolution maps, and conceptual structure analyzes, enabling the identification of dominant themes, emerging topics, and research gaps. This is a niche field with moderate growth, concentrated in Mexico with limited international collaboration, and a thematic progression from compositional profiling and fermentation ecology toward applied approaches such as probiotic stabilization, synbiotic product design, and enzymatic valorization. Core motor themes included fructans, fructooligosaccharides, inulin, and gut microbiota modulation, while emerging clusters highlighted encapsulation strategies, circular bioeconomy models, and sustainable bioprocessing of Agave residues. Highly cited studies bridged microbial community analyzes, technological optimization, and functional food applications, illustrating a transition from traditional ecological knowledge to modern industrial innovation. These findings demonstrated the evolving interdisciplinary nature of aguamiel research and underscored the need for standardized methodologies, expanded clinical validation, and broader international collaboration. The study provided an integrated overview of the field, supporting future efforts to harness aguamiel’s functional potential and position it within sustainable food systems.
Hydrocotyle sibthorpioides (L.) Lam., a widely distributed herb of the Araliaceae, is of interest for its long-standing ethnomedicinal use, chemically diverse constituents, and broad pharmacological promise. This review synthesizes current evidence on ethnobotany, phytochemistry, and bioactivity, and delineates priorities for translation. Traditional applications in Chinese, Ayurvedic, and Southeast Asian practices include management of fever, inflammation, hepatic and dermatologic complaints, and cognitive symptoms. Phytochemical investigations report triterpenoid saponins (e.g., asiaticoside, madecassoside), flavonoids (e.g., quercetin, rutin), phenolic acids (e.g., rosmarinic, chlorogenic), phytosterols, and lignans that plausibly underlie activity. Preclinical studies demonstrate antioxidant, anti-inflammatory, hepatoprotective, wound-healing, antimicrobial, neuroprotective, anticancer, antidiabetic, and immunomodulatory effects, broadly consistent with traditional claims. However, major gaps remain: limited human data, incomplete mechanism-of-action mapping across shared signaling axes, non-standardized extraction and characterization, uncertain dose–exposure–response relationships, and an underdeveloped safety dossier. To enable evidence-based use, future work should (i) standardize extracts with marker-guided specifications; (ii) conduct GLP toxicology beyond acute testing (subchronic, genotoxicity, and, where relevant, reproductive/developmental endpoints); (iii) characterize human pharmacokinetics and screen for herb–drug interactions; and (iv) undertake well-designed Phase I/II trials in indications best supported by preclinical data. Addressing these priorities will improve reproducibility, clarify clinical relevance, and support the responsible integration of H. sibthorpioides into modern phytotherapy.
A kinetic study on the preparation of an azo dye from the reaction between 1,4-di ((E)-chlorodiazenyl) benzene and p-anisidine (4-methoxy-aniline), was conducted at 290 K, with a maximum absorption wavelength (lmax) of 398 nm. The reaction was carried out in an acidic medium (pH = 5.27), under optimal conditions determined via UV-visible spectroscopy, at a concentration of 0.001 M. The resulting stoichiometric p- anisidine;azo reagent ratio was 1:2 in aqueous solution. The rate of dye formation was monitored under these conditions, with the rate constant reaching a maximum at 310 K (0.0765 min-1) and exhibiting a minimum at 280 K (0.0395 min-1). Furthermore, the formation of the dye followed pseudo-first-order kinetics relative with p-anisidine. The half-life (t 1/2) of the reactions at different temperatures was calculated as follows: 9.1, 10.8, 13.4, and 17.6 min at 310, 300, 290, and 280 K, respectively.
Oral gingivitis with mixed biofilms, specifically in immune-debilitated patients, is of great medical concern. The ability of the yeast Candida albicans to produce strong mixed biofilms with the oral bacterium Streptococcus mutans complicates the medical treatment and immunological response in those patients. To investigate how specific oral Streptococcus species influence Candida albicans biofilm formation, hyphal transformation, and biofilm stability in dual-species biofilms. A total of 100 samples (50 cancer patients and 50 non-cancer patients) suffering from oral gingivitis. Cancer patients were collected from different grades in Nanakali Hospital in Erbil, and non-cancer patients from Khanzad and Rzgary attended dentists’ clinics in the teaching hospital in Erbil, during the period of April 2024 to October 2024. Only 21 clinical isolates of Streptococcus spp. and 24 of Candida albicans. The identification of the fungal and bacterial isolates was conducted using morphological analysis, selective media for both microorganisms, and molecular identification via Multiplex Nested Polymerase Chain Reaction. The experimental and laboratory work was performed in the microbiology laboratories in the Research Center of Salahaddin University-Erbil. The results elucidated that these microorganisms, when occurring together, have a great potential to form biofilms both in vitro and in vivo. This exposes a medical challenge in the treatment of such infections, as biofilm eradication and removal require extensive efforts. The study also emphasizes new records of three species of Streptococcal bacterium (Streptococcus parauberis, Streptococcus thermophilus, and Streptococcus sobrinus), which, to our knowledge, is the first time for these strains to be isolated in the Erbil, Iraq.
In the current study, eco-friendly, simple, accurate, and selective univariate techniques were validated to evaluate a quinary mixture consisting of Rabeprazole (RB), Lansoprazole (LN), Amoxicillin (AM), Levofloxacin (LV), and paracetamol (PR) in the laboratory-prepared mixture and tablet formulations. Novel approaches, including pure spectrum extraction (PSE), the pure component contribution algorithm (PCCA), and constant multiplication (CM) were developed. Each method was combined with subtraction spectrum (SS) to determine each drug at its respective λmax. The extended spectra of LV at 298 nm were extracted using (CM-SS), the D0 spectra of RB at 288 nm and LN at 286 nm were retrieved with (PSE-SS). PR and AM were determined at 250 nm and 234 nm, respectively, using (PCCA-SS). The spectral ratio factor (SRF) and the spectral contrast angle (COSƟ) were established to measure the accuracy and validity of the retrieved signals. The results were statistically compared with reported methods, and validated per ICH guidelines. Additionally, the greenness and whiteness were assessed of the proposed techniques along with the reported methods, the results indicate the sustainability and echo-friendly of proposed techniques.
The electrochemical behavior of copper in choline chloride/ethylene glycol (Ethaline), a deep eutectic solvent (DES), and its amino acid-inhibited solutions (alanine, glycine, and leucine) was investigated using linear sweep voltammetry (LSV) and potentiodynamic polarization measurements (PDP). The Tafel slopes and polarization curves illustrate the different electrochemical processes at play, highlighting the impact of charge transfer kinetics, mass transport phenomena, and amino acid adsorption on the copper surface. In uninhibited Ethaline, the anodic current converted from charge transfer based current to mixed charge transfer-mass transfer behavior at potentials 0.03 V more positive than the corrosion potential (Ecorr.), eventually adopting a mass transfer-controlled shape beyond 0.3 V. The addition of amino acids modified the electrochemical response, with glycine and leucine shifting the corrosion potential to more noble values, indicating enhanced corrosion resistance. Alanine exhibited a pseudo-passivation effect, shifting the pseudo-passivation current by 0.12 V toward more positive potentials. The cathodic current was reduced in the presence of amino acids, though the change was less obvious compared to the anodic behavior. Binary amino acid mixtures further influenced the polarization behavior, with the alanine/leucine combination showing the strongest inhibition effect. The significant difference between forward and backward Ecorr. is observed which offers deep insights into dynamic surface interactions, film stability, and the effectiveness of corrosion inhibitors. The study highlights the complex interplay of organic adsorption, chloride complexation, and mass transport limitations in DESs, underscoring their distinct electrochemical behavior compared to aqueous systems. These findings provide insights into the corrosion inhibition mechanisms of amino acids in DESs and their potential applications in controlling metal dissolution.
In this paper, a novel metaheuristic called the Nudibranch Optimization Algorithm (NUOA) is developed. The algorithm is derived from the various modes that these nudibranchs use to look for their next meal and, in turn, ways of avoiding any threats. However, this algorithm evaluates a benchmark set of functions, encompassing all the executed analysis tasks pertinent to the CEC2019 test suites, as well as the integrated classical functions. These findings demonstrate that, in general, NUOA provides a better opportunity to explore and exploit than all of the proposed algorithms for NUOA. Therefore, the evaluation of statistical data and proofs validates the performance improvement, demonstrating NUOA's superiority over the other algorithms by at least one order of magnitude. Upon closer examination of the parameters, it becomes clear that NUOA maintains its functionality across various optimization tasks. We also use some of the most popular optimization algorithms, including particle swarm optimization (PSO), artificial bee colony (ABC), pelican optimization algorithm (POA), and fitness dependent optimizer (FDO), and compare them with NUOA.
Preprint: In the current study, wastepaper was employed to produce bioethanol using physicochemical treatment. This waste was treated with diluting sulfuric acid at various concentrations and ratios to release monosaccharides at a high level, which were converted into bioethanol by fermentation processes using S. cerevisiae. The best yield was obtained at a concentration of 1.5% acid at a ratio of 1 g/10 mL that yielded 32%. To increase the purity of the bioethanol, distillation and molecular sieve as a drying agent were utilized, resulting in a bioethanol concentration of 98%. Bioethanol produced bioethanol was characterized using FTIR and NMR spectroscopy. In addition, the bioethanol was blended with regular gasoline at different ratios to produce E0, E6, E8, E10 and E12 mixtures. The ASTM methods was used to evaluate these mixtures, including RVP, RON, density and water content. It was observed that RVP values decreased while the density increased with increasing ethanol content in the mixture. However, the water content and RON of bioethanol-gasoline blends increased gradually with the addition of ethanol. The important aspect of this study is the production of bioethanol using an available and cheap feedstock using optimal conditions.
The most common approach to evaluating the stability of nanofluids is sedimentation analysis; however, further research is needed to confirm stability and determine optimal operating conditions for various nanofluid compositions. This study aims to systematically investigate the stability of nanofluids containing different volume fractions (0.1 wt%, 0.2 wt%, and 0.3 wt%) of Al₂O₃, CuO, and TiO₂ nanoparticles dispersed in distilled water (DW). Several homogenization techniques were employed, including the use of specific surfactants sodium hydrogen carbonate (NaHCO₃), carboxymethyl cellulose (CMC), and ultrasonic treatment, to enhance nanoparticle dispersion and prevent aggregation. A two-step preparation method was used to ensure proper integration of nanoparticles into the base fluid. Experimental results revealed that CuO/DW nanofluids exhibited sedimentation stability for up to 58 days without surfactant and up to 77 days with CMC at 0.3 wt%, followed by TiO₂/DW nanofluids, which showed an increase in stability from 7 days without surfactant to 32 days with CMC at 0.1 wt%. Al₂O₃/DW nanofluids demonstrated sedimentation stability ranging from 23 to 52 days depending on concentration and surfactant presence. Notably, the sedimentation stability of TiO₂ nanofluids was significantly improved due to electrostatic repulsion induced by CMC. Additionally, adjusting the pH and incorporating NaHCO₃ further enhanced the stability of hybrid nanofluids by minimizing nanoparticle agglomeration and ensuring uniform dispersion throughout the suspension. This study contributes to the development of more stable and efficient nanofluid systems by demonstrating the critical roles of surfactant type, concentration, and ultrasonic treatment in improving the stability of metal oxide-based nanofluids.
The substitution of natural aggregate with recycled concrete aggregate in concrete is currently being researched to address increasing environmental and sustainability concerns. Recycled concrete aggregate is sustainable for the environment and is used in concrete production. This research addresses the experimental evaluation of recycled concrete aggregate (RCA) as a substitute for natural aggregate (NA) in interior slab-column connections. Small-scale internal slab-column connections were subjected to a concentrated load applied through the column until failure happened. The primary test variables were slab thickness and concrete type and the slabs were designed to fail in shear. All slabs had identical dimensions and a reinforcement ratio of 1%. The article provides a thorough explanation of the experimental procedure, tests, and outcomes, together with an overview of all results. The punched shear capabilities have been determined from the test results and compared with the estimated values based on the ACI code equations. The evaluation of the slabs was conducted via a comparison of load capacity, failure modes, load-deflection, concrete strain, steel strain, and cracking patterns. The test findings indicated that the presence of RCA in RC slabs resulted in only a 5 percent reduction in ultimate capacity and an enhancement in deformability compared to normal concrete (NAC) slabs. The deflection of the RCA slab was minimized by increasing its thickness; hence, its capacity was improved.
