Indus University

This research discusses the contributions of AI-enabled talent acquisition and sustainable entrepreneurial orientation to the strategic drivers of sustainable business performance, with a focus on the mediating effect of environmental innovation capability and sustainable human capital agility, and the moderating effect of environmental uncertainty. The study is based on sustainability strategy, dynamic capabilities, and contingency theory, as well as on digital HRM and entrepreneurial behaviors as centralized processes that enable SMEs to develop environmentally responsible and resilient business outcomes. The survey involved 837 senior SME employees and entrepreneurs in the United States, using a cross-sectional quantitative design. The hypothesized causal relationships were tested using structural equation modeling (PLS-SEM), which helped the researchers assess predictive validity, whereas machine-learning models, such as neural networks, random forests, and regularized linear regression, implemented in JASP, enhanced robustness. The results show that AI-based talent acquisition and sustainable entrepreneurial orientation are very effective in devising strategies for sustainable business performance. Both sustainable human capital agility and environmental innovation capability are potent mediators, showing how digitalized talent systems and sustainability-focused entrepreneurial strategies translate into eco-innovation and business social responsibility outcomes. Environmental uncertainty only modulates the environmental innovation capability pathway, suggesting that eco-innovation is especially effective in turbulent, unpredictable environments. Machine-learning validation confirms strong predictive accuracy, and neural networks perform optimally. The proposed research contributes to the sustainability and business strategy literature by combining SEM and machine learning to produce complementary explanatory and predictive information. It provides practical advice to SMEs on developing nimble, innovative, and environmentally sustainable business models that can succeed amid technological shifts and environmental uncertainty.

Brand anthropomorphism, defined as the act of personifying brands, has gained significant attention from research scholars within the current market. The present research investigates how brand anthropomorphism, a powerful branding strategy, promotes brand attachment, particularly in the confectionery industry. The study employs the theory of attachment and anthropomorphism. Responses from 463 participants were collected via social media, specifically from those who interacted with anthropomorphised brands used in the confectionery industry. PLS-SEM was employed to analyse the relations between variables and examine the mediating role of attachment with the brands. Results confirmed that anthropomorphic brands significantly enhance attachment and help strengthen brand love, thus inspiring consumers towards a positive electronic word-of-mouth (eWOM). The analysis reveals that brand attachment fully mediates the effect of anthropomorphism on brand love and partially mediates its impact on eWOM. The results propose that brand humanisation can be a powerful approach to building emotional connections, driving consumer encouragement, and strengthening brand perceptibility through eWOM. The research provides valuable insights for marketers, highlighting the importance of anthropomorphism in fostering stronger consumer relationships with the brand, leveraging these bonds to establish long-term relationships and promote a positive eWOM.

The performance of CVD-coated carbide inserts (TiCN/Al2O3) in hard turning AISI 4340 steel at cutting speeds of 60, 95, 180, and 250 m/min, under both dry and wet conditions are investigated. The goals were to evaluate tool wear, surface roughness, and wear mechanisms over different machining conditions. Surface roughness Ra value was noticed, and it dropped to Ra = 0.30 & micro;m at 180 m/min but increased at 250 m/min due to vibration, edge instability, and wear. Flank wear rose with cutting speed: 186 & micro;m at 60 m/min, 265 & micro;m at 180 m/min, 542 & micro;m at 250 m/min (dry), and 692 & micro;m (wet), exceeding ISO tool life (VB = 300 & micro;m) due to edge breakage, flaking, and adhesion. The examination of the tool surface by SEM and EDS revealed abrasion and slight coating delamination at low speeds, adhesion and oxidation at intermediate speeds, and catastrophic tool failure at high speeds.

This paper provides a comparative research on hybrid watermarking methods in medical image security. Securing medical information like patient records and medical images, when stored and transferred is a significant challenge. Conventional watermarking techniques might not offer adequate protection, resilience and authentication. Hence, hybrid methods involving the integration of watermarking and encryption, as well as, spatial/frequency domain methods are more useful in improving security. The paper contrasts different hybrid methods in terms of image quality and strength in terms of Peak Signal-to-Noise Ratio (PSNR). PSNR values in the surveyed methods are reported to be between 39 dB and 59 dB, which suggests better imperceptibility and quality of reconstruction. Medical data like CT scans, MRI, X-ray and ultrasound needs confidentiality, integrity checks and secure access. The results indicate that hybrid watermarking systems offer high confidentiality, robustness, authentication and protection compared to traditional watermarking systems.

The present work introduces a matrix analogue of a general class of q-polynomials { S_n(A,L,m;x|q): A∈ℂ^r× r, L∈{0}∪ℕ, m∈ℕ, x∈ℝ, 0