Polyurethane is a multipurpose polymer with valuable mechanical, thermal, and chemical stability, and countless other physical features. Polyurethanes can be processed as foam, elastomer, or fibers. This innovative overview is designed to uncover the present state and opportunities in the field of polyurethanes and their nanocomposite sponges. Special emphasis has been given to fundamentals of polyurethanes and foam materials, related nanocomposite categories, and associated properties and applications. According to literature so far, adding carbon nanoparticles such as graphene and carbon nanotube influenced cell structure, overall microstructure, electrical/thermal conductivity, mechanical/heat stability, of the resulting polyurethane nanocomposite foams. Such progressions enabled high tech applications in the fields such as electromagnetic interference shielding, shape memory, and biomedical materials, underscoring the need of integrating these macromolecular sponges on industrial level environmentally friendly designs. Future research must be intended to resolve key challenges related to manufacturing and applicability of polyurethane nanocomposite foams. In particular, material design optimization, invention of low price processing methods, appropriate choice of nanofiller type/contents, understanding and control of interfacial and structure-property interplay must be determined.

A comprehensive proteomic analysis was carried out to evaluate leaf proteome changes of Brassica napus cultivars as an important oilseed crop inoculated with the bacterium Pseudomonas fluorescens FY32 under salt stress. Based on the physiochemical characteristics of canola, Hyola308 was a tolerant and Sarigol was a salt sensitive cultivar. Gel-based proteomics indicated that proteins related to energy/metabolism, cell/membrane maintenance, signalins, stress, and development respond to salt stress and bacterial inoculation in both cultivars. Under salt stress, Hyola308 launches mechanisms similar to Sarigol, but the tolerance was related to consuming less energy consumption than Sarigol for launching the proper pathway/mechanism. Inoculation with plant growth promoting bacteria promotes relative growth rate and net assimilation rate; causes increase in soluble sugar content (12–32% varing to cultivars and salt treatments), as an osmo-protectant, in leaves of Sarigol and Hyola308 in control and salt stress conditions. The groups of proteins that are affected due to inoculation (18 and14 functional groups in Hyola308 and Sarigol, respectively) are varying to stress-influenced groups (10 and 6 functional groups in Hyola308 and Sarigol, respectively) that might be because of regulating tolerance mechanism of plant and/or plant-growth promoting bacteria inoculation. Furthermore, it is recognized that P. fluorescens FY32 has a dual effect on the cultivars including a pathogenic effect and a growth promoting effect on both cultivars under salt stress.

This research investigates the effects of drying on some selected vegetables, which are Telfaria occidentalis, Amaranthu scruentus, Talinum triangulare, and Crussocephalum biafrae. These vegetables were collected fresh, sliced into smaller sizes of 0.5 cm, and dried in a convective dryer at varying temperatures of 60.0 °C, 70.0 °C and 80.0 °C respectively, for a regulated fan speed of 1.50 ms‒1, 3.00 ms‒1 and 6.00 ms‒1, and for a drying period of 6 hours. It was discovered that the drying rate for fresh samples was 4.560 gmin‒1 for Talinum triangulare, 4.390 gmin‒1for Amaranthu scruentus, 4.580 gmin‒1 for Talinum triangulare, and 4.640 gmin‒1 for Crussocephalum biafrae at different controlled fan speeds and regulated temperatures when the mass of the vegetable samples at each drying time was compared to the mass of the final samples dried for 6 hours. The samples are considered completely dried when the drying time reaches a certain point, as indicated by the drying rate and moisture contents tending to zero. According to drying kinetics, the rate of moisture loss was extremely high during the first two hours of drying and then steadily decreased during the remaining drying duration. The rate at which moisture was removed from the vegetable samples after the drying process at varying regulated temperatures was noted to be in this trend: 80.0 °C > 70.0 °C > 60.0 °C and 6.0 ms‒1 > 3.0 ms‒1 > 1.5 ms‒1 for regulated fan speed. It can be stated here that the moisture contents has significant effects on the drying rate of the samples of vegetables investigated because the drying rate decreases as the regulated temperatures increase and the moisture contents decrease. The present investigation is useful in the agricultural engineering and food engineering industries.

Metal oxide-based nanohybrids have become multipurpose materials that connect basic nanoscience with useful technology uses. They are appealing for a variety of sectors, from biology to energy and environmental remediation, due to their tunable physicochemical features and synergistic interactions. The main synthesis approaches—physical, chemical, and green/biological—are presented in a cohesive manner in this review, emphasizing their benefits, drawbacks, scalability, and appropriateness for various application requirements. Characterization methods including spectroscopy, diffraction, and microscopy are presented as crucial connections that link final functional performance with structure, composition, and morphology in addition to being analytical instruments. Additionally, the review incorporates new advancements such as data-driven intelligent material design, sustainable synthesis utilizing microbes and plant extracts, and machine learning-assisted process optimization. All things considered, this work provides a coherent overview linking synthesis techniques, property assessment, and application potential, providing insights that can direct the future development of effective, environmentally friendly metal oxide nanohybrids designed for practical technological deployment.

Within this broader analytical framework, this paper seeks to explore the apparent impact of digital transformation on employee relations within the context of listed companies. A theoretical model is proposed, positing digital transformation as the independent variable, employee relations as the dependent variable, and what might be characterized as cultural fit as a potential moderating variable. Based on an analysis of 482 ostensibly valid questionnaires collected from a sample of 500 A-share listed companies in China, what seems to emerge from these findings is that the mean score for the digital transformation scale was approximately 3.62, which tends to point toward a stage of local optimisation. The mean scores for the employee relations and corporate cultural fit scales were found to be 3.55 and 3.58, respectively. What the evidence appears to reveal is that digital transformation seems to be substantially positively correlated with employee relations (r ≈ 0.62, p < 0.01), and corporate cultural fit appears to share a similar positive correlation with both. What the analysis tends to support, furthermore, is that digital transformation appears to have a substantial positive impact on employee relations (β ≈ 0.58, p < 0.01). What seems especially noteworthy in this analytical context is that corporate culture fit seems to lend support to what may represent a positive moderating role (β ≈ 0.21, p < 0.05). In the high-fit group, the impact of digital transformation on employee relations appears to tend to suggest it is seemingly stronger (β ≈ 0.68, p < 0.01). What appears to emerge from this evidence, therefore, is the construction of a tentative model of this three-way relationship, ostensibly providing a basis for companies to balance technological innovation and humanistic care.

Keywords: Digital transformation; listed companies; employee relations; corporate culture compatibility; moderating effects

With the deep integration of artificial intelligence technology in education, the development of AI integration capabilities among pre-service teachers—as the core of future educational human resources—has become crucial for enhancing educational quality and driving digital transformation in education. Based on the AI-TPACK (Artificial Intelligence-Technological Pedagogical Content Knowledge) theoretical framework, this study employs questionnaire surveys and structural equation modeling to explore the structural characteristics, influencing factors, and formation mechanisms of AI-TPACK competencies among pre-service teachers in Chinese universities. Findings indicate that while pre-service teachers demonstrate moderately high overall AI-TPACK levels, their technical knowledge (AI-TK) and technological integration competencies (e.g., AI-TPK, AI-TCK) remain relatively weak. School technical support, technological attitudes, and technological competence significantly influence their AI-TPACK capabilities, with institutional level and teaching experience serving as important external moderating factors. Building on these findings, this paper proposes a systematic framework for developing pre-service teachers' AI integration capabilities from a human resource development perspective. This framework encompasses four dimensions: curriculum optimization, practice enhancement, resource support, and policy guidance. It aims to provide theoretical foundations and practical pathways for pre-service teacher training and teacher human resource development in higher education institutions.