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A novel triazene-anthracene-based fuorescent aminal linked porous organic polymer (TALPOP) was prepared via metal free-Schif base polycondensation reaction of 9,10-bis-(4,6-diamino-S-triazin2-yl)anthracene and 2-furaldehyde. The polymer has exceptional chemical and thermal stabilities and exhibit good porosity with Brunauer–Emmett–Teller surface area of 401 m2 g−1. The combination of such porosity along with the highly conjugated heteroatom-rich framework enabled the polymer to exhibit exceptional iodine vapor uptake of up to 314 wt % and reversible iodine adsorption in solution. Because of the inclusion of the anthracene moieties, the TALPOP exhibited excellent detection sensitivity towards iodine via forescence quenching with Ksv value of 2.9 × 103 L mol−1. The cost effective TALPOP along with its high uptake and sensing of iodine, make it an ideal material for environmental remediation.

Leptospirosis is one of the most widespread zoonotic diseases and can infect both humans and animals worldwide. Healthy cat, as a potential source of exposure to humans, are likely underestimated owing to the lack of overt clinical signs associated with Leptospira spp. infection in this species. The aim of the study was to determine the exposure, shedding, and carrier status of leptospires in shelter cats in Malaysia by using serological, molecular, and bacteriological methods. For this study, 82 healthy cats from two shelters were sampled. The blood, urine, and kidneys were tested using the microscopic agglutination test (MAT), polymerase chain reaction (PCR), and bacterial culture. On the basis of serological, molecular, and/or culture techniques, the total detection of leptospiral infection was 29.3% (n = 24/82). Through culture techniques, 16.7% (n = 4/24) of the cats that tested positive were carriers with positive kidney cultures, and one cat was culture positive for both urine and kidney. The Leptospira spp. isolates were identified as pathogenic L. interrogans serovar Bataviae through serological and molecular methods. Through serological techniques, 87.5% (n = 21/24) had positive antibody titers (100-1600) and most of the Bataviae serogroup (n = 19/21). Using PCR, 16.7% (n = 4/24) of cats were shown to have pathogenic Leptospira spp. DNA in their urine. Furthermore, three out of four culture positive cats were serology negative. The present study reports the first retrieval of pathogenic leptospires from urine and kidneys obtained from naturally infected cats. The results provide evidence of the potential role of naturally infected cats in the transmission of leptospires. Additionally, leptospiral infection occurs sub-clinically in cats. The culture isolation provides evidence that healthy cats could be reservoirs of leptospiral infection, and this information may promote the development of disease prevention strategies for the cat population.

Waste cooking oil (WCO) biodiesel has some disadvantages, such as poor cold flow properties, low oxidation stability, and flash point during storage. These poor physicochemical properties can be improved by different ways, such as the addition of non-edible oil. The aim of this study to analyse physicochemical properties of the biodiesel made by between WCO and Schleichera oleosa (SO). The biodiesel produced with 70:30% of WCO and SO respectively as crude oil, further introducing of different KOH-based catalyst into this oil to obtained the methyl ester. The optimum yield transesterification process are 94% with 60 min. of the reaction time, 1 wt.% KOH, and 12:1 molar ratio the methanol to oil. On the other hand, the Schleichera oleosa blend shows oxidation stability at 6.8 h and 3.3 h for Waste cooking oil methyl ester (WCME). The reduction of cold flow and, on the contrary, the flash point increase were obtained with a 70:30% ratio of WCO and SO. The cold flow properties and flash point of the fuel. Thus, mixed WCO and Schleichera oleosa oil improve the physiochemical properties such as oxidation stability, flash point, and cold flow of biodiesel without the need for synthetic antioxidants.

The thermal conductivities of selected deep eutectic solvents (DESs) were determined using the modified transient plane source (MTPS) method over the temperature range from 295 K to 363 K at atmospheric pressure. The results were found to range from 0.198 W·m−1·K−1 to 0.250 W·m−1·K−1. Various empirical and thermodynamic correlations present in literature, including the group contribution method and mixing correlations, were used to model the thermal conductivities of these DES at different temperatures. The predictions of these correlations were compared and consolidated with the reported experimental values. In addition, the thermal conductivities of DES mixtures with water over a wide range of compositions at 298 K and atmospheric pressure were measured. The standard uncertainty in thermal conductivity was estimated to be less than ± 0.001 W·m−1·K−1 and ± 0.05 K in temperature. The results indicated that DES have significant potential for use as heat transfer fluids.

The new era of nanomedicine offers significant opportunities for cancer diagnostics and treatment. Magnetic nanoplatforms could be highly effective tools for cancer diagnosis and treatment in the future. Due to their tunable morphologies and superior properties, multifunctional magnetic nanomaterials and their hybrid nanostructures can be designed as specific carriers of drugs, imaging agents, and magnetic theranostics. Multifunctional magnetic nanostructures are promising theranostic agents due to their ability to diagnose and combine therapies. This review provides a comprehensive overview of the development of advanced multifunctional magnetic nanostructures combining magnetic and optical properties, providing photoresponsive magnetic platforms for promising medical applications. Moreover, this review discusses various innovative developments using multifunctional magnetic nanostructures, including drug delivery, cancer treatment, tumor-specific ligands that deliver chemotherapeutics or hormonal agents, magnetic resonance imaging, and tissue engineering. Additionally, artificial intelligence (AI) can be used to optimize material properties in cancer diagnosis and treatment, based on predicted interactions with drugs, cell membranes, vasculature, biological fluid, and the immune system to enhance the effectiveness of therapeutic agents. Furthermore, this review provides an overview of AI approaches used to assess the practical utility of multifunctional magnetic nanostructures for cancer diagnosis and treatment. Finally, the review presents the current knowledge and perspectives on hybrid magnetic systems as cancer treatment tools with AI models.

Cut flowers and floral waste (CFW) is a major concern in the present era. This study emphasizes the reuse of cut flowers as a neat bioadsorbent and activated carbon (AC). The biomass from the cut flowers was utilized as a neat bioadsorbent for the removal of the antibiotic levofloxacin and lead ions from water. The results revealed that the neat bioadsorbent was able to remove 60% levofloxacin and 45% of lead ions. Upon chemical activation of the CFW (using KOH), almost all levofloxacin and more than 99% of lead ions were removed. Physical activation (using CO 2 ) gave a material that removed 90% of levofloxacin and 85% of lead ions. The adsorption of levofloxacin and lead ions on all the adsorbents followed Langmuir isotherms and pseudo-second-order kinetic model. The results have been further explained via the prediction of interaction energies between the adsorbates and adsorbents using COSMO-RS simulation.

In the realm of bioprocess technology, microbial fuel cells (MFCs) are regarded as a noteworthy innovation that can simultaneously bioremediate wastewater and utilise as renewable energy applications. The investigation began with synthesizing composite proton exchange membrane (PEM) with sulfonated polysulfone (SPSF) and sulfonated chitosan (SCS) as a separator for MFCs. A composite membrane has been developed by crosslinking a microporous SPSF substrate with a thin layer of chitosan (CS). The membrane was then evaluated for its suitability in MFCs which employ dewatered sludge. The appearance and physico-mechanical properties of this composite were thoroughly examined using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), proton conductivity measurements, back-end titration tests, and water uptake studies. Attempts were made to enhance the connection between the duo polymers such as PSF and CS by providing surface changes with the incorporation of sulfonation properties. As a result, two novel types of composite materials were developed: (SPSF/CS) and (SPSF/SCS), which were made by altering a PSF membrane’s surface before adding a chitosan layer using the non-solvent phase inversion technique. The proton conductivity of SPSF/CS and SPSF/SCS composites was measured and contrasted with that of unmodified PSF. The composite, SPSF/SCS-1, 0.5 wt%, showed greater proton conductivity and ion exchange capacity (IEC) (1.7 meq/g, 0.061 S/cm) than the unaltered PSF (0.99 meq/g, 0.009 S/cm). According to the MFCs performance, the SPSF/SCS-1, 0.5 wt% membrane demonstrated a substantial electricity production compared to pristine PSF 38.57 mW/m 2 and 0.449 mW/m 2 . These results vividly depicted that the composite SPSF/SCS PEM increases the productivity of dual-chamber MFCs. Article Highlights Monitored the performance of MFCs with presence of polymeric proton exchange membrane Efficiency of sulfonated polysulfone in different types of solvents approached in MFCs The power generation associated with the ion exchange capacity of the membrane. The maximum power generated about 19.1 mW/m 2 with the ion exchange capacity of 1.8 meq/g

Artificial Intelligence (AI) has emerged as a transformative force across various domains, including education. In fine arts education, AI offers unprecedented opportunities to innovate teaching methodologies, foster creativity, and enhance student engagement. While significant advancements have been made in integrating AI into fine arts education through techniques such as Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNNs), and Large Language Models (LLMs), there is a notable lack of a comprehensive review summarizing these developments. To bridge this gap, this study systematically examines the most adopted applications of AI in fine arts education from 2019 to 2024. Utilizing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, an exhaustive review of 78 studies was conducted, focusing on the types of technologies commonly employed by AI in fine arts education and the specializations within fine arts education that leverage AI. This review further provides a structured analysis of existing literature, focusing on their methodologies, objectives, and trends. The study highlights the transformative potential of AI in fine arts education while identifying critical gaps and challenges that require further investigation. By offering a comprehensive analysis, it serves as a roadmap for educators, researchers, and policymakers to harness AI’s capabilities in the fine arts domain effectively. How Artificial Intelligence Is Changing Fine Arts Education: A Global Review of New Tools, Teaching Methods, and Challenges from 2019 to 2024 This study explores how artificial intelligence (AI) is being used to transform fine arts education. Over the past few years, AI has started to play an important role in classrooms and studios, helping students and teachers in new and exciting ways. AI tools can now support drawing, music, performance, and even creative writing, making art lessons more interactive and tailored to each student’s needs. To better understand this trend, the study reviewed 78 research papers published between 2019 and 2024. These papers discussed how technologies like image-generating programs, virtual and augmented reality, and language-based chatbots (such as ChatGPT) are used in fine arts education. The review found that AI is most commonly used in visual arts education-like painting and design-while other areas like music, theater, and creative writing are still catching up. The findings show that AI can enhance creativity, help students express their ideas in new ways, and make learning more personal and engaging. For teachers, AI offers tools to better understand student progress and provide real-time feedback. However, the study also points out challenges, such as the need for teacher training, the cost of new technologies, and ethical questions about using AI to create art. Overall, this review helps educators, school leaders, and policymakers understand where AI is being used effectively in fine arts education, where it’s still missing, and what can be done to ensure that all students can benefit from these powerful new tools. It encourages schools to consider how AI can support-not replace-human creativity in the classroom.

Vibration in the shaft of a centrifugal pump arises from various factors, including the spacing between clutches, belt thickness, width, and their positioning within the clutch assembly. Vibration serves as a vital diagnostic tool for assessing machinery, offering insights into both motion and translation. Understanding vibrations and analyzing corresponding data are essential for effective maintenance and troubleshooting protocols. By leveraging this knowledge, companies can mitigate downtime, enhance productivity, and extend the operational lifespan of their machinery. Vibration stems from cyclic forces acting upon machine components, triggering energy release within the structure and resulting in oscillations. Excessive vibration not only generates noise but also compromises pump performance and jeopardizes critical components, notably the shaft and bearings. The objective of this study is to monitor and analyze vibration in centrifugal pumps equipped with modified belt connections. Various configurations of belt thickness, width, distance, and positioning were explored. Real-time data was gathered using accelerometer sensors to capture X, Y, and Z-axis values, subsequently converted from analog to digital format. Among the configurations tested, the Outside-Inside belt positioning, with belt dimensions of 6.5mm thickness, 150mm width, and a 40mm distance, exhibited the lowest average vibration value at 8.72mm/s. However, according to ISO 10816 standards, this measurement falls within the unsatisfactory category, indicating the need for further refinement in pump design and maintenance practices.

The need for energy resources is growing all the time, which means that more fossil fuels are needed to provide them. People prefer to consume chicken as a source of protein, and this creates an abundance of waste. Thus, microbial fuel cells represent a new technological approach with the potential to generate electricity through the action of electrogenic bacteria toward chicken manure, while reducing the abundance of chicken manure. This study investigated the effect of different pretreatment (thermal, alkaline, and sonication pretreatment) of chicken manure to improve the performance of a membrane-less microbial fuel cell (ML-MFC). Statistical response surface methodology (RSM) through a central composite design (CCD) under a quadratic model was conducted for optimization of the ML-MFC performance focusing on the COD removal efficiency (R2 = 0.8917), biomass (R2 = 0.9101), and power density response (R2 = 0.8794). The study demonstrated that the highest COD removal (80.68%), biomass (7.8539 mg/L), and power density (220 mW/m2) were obtained when the pretreatment conditions were 140 °C, 20 kHz, and pH 10. The polarization curve of the best condition of ML-MFC was plotted to classify the behavior of the ML-MFC. The kinetic growth of Bacillus subtillis (BS) showed that, in treated chicken manure, the specific growth rate µ = 0.20 h−1 and doubling time Td = 3.43 h, whereas, in untreated chicken manure, µ = 0.11 h−1 and Td = 6.08.