Modified chitosan hybrids were obtained via chemical reaction of chitosan with two pyrazole aldehyde derivatives to produce two chitosan Schiff bases, Cs-SB1, and Cs-SB2, respectively. FTIR spectroscopy and scanning electron microscopy confirmed both chemical structures and morphology of these Schiff bases. Thermal gravimetric analysis showed an improvement of thermal properties of these Schiff bases. Both chitosan Schiff bases were evaluated in a batch adsorption approach for their ability to remove Cu(II) ions from aqueous solutions. Energy dispersive X-ray for the Schiff bases adsorbed metal ions in various aqueous solutions was performed to confirm the existence of adsorbed metal ions on the surface substrate and their adsorptive efficiency for Cu(II) ions. Results of the batch adsorption method showed that prepared Schiff bases have good ability to remove Cu(II) ions from aqueous solutions. The Langmuir isotherm equation showed a better fit for both adsorbents with regression coefficients (R² = 0.97 and 0.99, respectively) with maximum adsorption capacity for Cu(II) of 10.33 and 39.84 mg/g for Cs-SB1 and Cs-SB2, respectively. All prepared compounds, pyrazoles and two chitosan Schiff bases, showed good antimicrobial activity against three Gram +ve bacteria, three Gram –ve bacteria and Candida albicans, with varying degrees when compared to the standard antimicrobial agents.

Metal iodide materials as novel components of thermal biological and medical systems at the interface between heat transfer techniques and therapeutic systems. Due to their outstanding heat transfer coefficients, biocompatibility, and thermally activated sensitivity, metal iodides like silver iodide (AgI), copper iodide (CuI), and cesium iodide (CsI) are considered to be useful in improving the performance of medical instruments, thermal treatment processes, and diagnostics. They are examined for their prospective applications in controlling thermal activity, local heating therapy, and smart temperature-sensitive drug carrier systems. In particular, their application in hyperthermia therapy for cancer treatment, infrared thermal imaging for diagnosis, and nano-based drug carriers points to a place for them in precision medicine. But issues of stability of materials used, biocompatibility, and control of heat—an essential factor that would give the tools the maximum clinical value—remain a challenge. The present mini-review outlines the emerging area of metal iodides and their applications in medical technologies, with a special focus on the pivotal role of these materials in enhancing non-invasive, efficient, and personalized medicine. Over time, metal iodide-based systems scouted a new era of thermal therapies and diagnostic instrumentation along with biomedical science as a whole.

Recently, carbon nanocomposites have garnered a lot of curiosity because of their distinctive characteristics and extensive variety of possible possibilities. Among all of these applications, the development of sensors with electrochemical properties based on carbon nanocomposites for use in biomedicine has shown as an area with potential. These sensors are suitable for an assortment of biomedical applications, such as prescribing medications, disease diagnostics, and biomarker detection. They have many benefits, including outstanding sensitivity, selectivity, and low limitations on detection. This comprehensive review aims to provide an in-depth analysis of the recent advancements in carbon nanocomposites-based electrochemical sensors for biomedical applications. The different types of carbon nanomaterials used in sensor fabrication, their synthesis methods, and the functionalization techniques employed to enhance their sensing properties have been discussed. Furthermore, we enumerate the numerous biological and biomedical uses of electrochemical sensors based on carbon nanocomposites, among them their employment in illness diagnosis, physiological parameter monitoring, and biomolecule detection. The challenges and prospects of these sensors in biomedical applications are also discussed. Overall, this review highlights the tremendous potential of carbon nanomaterial-based electrochemical sensors in revolutionizing biomedical research and clinical diagnostics.

Mind map was a note-taking method proposed by Tony Buzan(1994). And later it is developed into eight modes of thinking maps by David Hyerle(2009), which has been widely used in English teaching. As a knowledge visualization learning tool, mind map could help students construct knowledge framework, sort out knowledge structure, expand thinking and enhance memory. This article will take the grade three class of Shijiao Qixing Primary School in Shijiao Country, Qingyuan City as a sample. The Shijiao Qixing Primary School is a village primary school which most of the students are left-behind children and there are about 30 teachers with an age of 40. Neither the teachers nor the students have experienced the mind mapping teaching method. The article will explore the application of mind mapping in a countryside primary school based on relevant theoretical knowledge and classroom practice.

This study explores the integration of data mining, customer relationship management (CRM), and strategic management to enhance the understanding of customer behavior and drive revenue growth. The main goal is the use of application of data mining techniques in customer analytics, focusing on the Extended RFM (Recency, Frequency, Monetary Value and count day) model within the context of online retailing. The Extended RFM model enhances traditional RFM analysis by incorporating customer demographics and psychographics to segment customers more effectively based on their purchasing patterns. The study further investigates the integration of the BCG (Boston Consulting Group) matrix with the Extended RFM model to provide a strategic view of customer purchase behavior in product portfolio management. By analyzing online retail customer data, this research identifies distinct customer segments and their preferences, which can inform targeted marketing strategies and personalized customer experiences. The integration of the BCG matrix allows for a nuanced understanding of which segments are inclined to purchase from different categories such as “stars” or “cash cows,” enabling businesses to align marketing efforts with customer tendencies. The findings suggest that leveraging the Extended RFM model in conjunction with the BCG matrix can lead to increased customer satisfaction, loyalty, and informed decision-making for product development and resource allocation, thereby driving growth in the competitive online retail sector. The findings are expected to contribute to the field of Infrastructure Finance by providing actionable insights for firms to refine their strategic policies in CRM.