DSM (India)

The present study investigates the relationship between working capital management and SME profitability. It also analyzes the impact of macroeconomic impulses on firm profitability through efficient management of working capital in the case of Indian small and medium scale enterprises over the time period spanning from 2010 to 2017 using Feasible Generalized Least Square (FGLS) regression models. The study concludes the negative relationship of account receivables together with a positive relationship of inventories and account payables with SME profitability. It implies the firm managers can maximize SME’s profitability by converting the credit sales to cash as early as possible, by increasing the days of accounts payable and following a conservative inventory management strategy. Changes in economic growth and commercial bank advances to small scale industries are the key macroeconomic determinants that are impacting SME profitability. The results from this paper may guide the firm managers to shape their working capital management strategies to maximize profitability. Policymakers may find the study interesting to identify the macroeconomic parameters that significantly influence Indian SMEs.

Bovine infertility is a major issue in dairy industry and it is primarily addressed by hormonal therapy. In present study we compared ovarian structure palpation based minimum hormonal utilization approach (KVK-RDDC protocol) with other estrus synchronization protocols. This study was conducted on 315 infertile cows kept in different managemental conditions i.e. Commercial dairy farms, villages and Gaushala’s in different areas of Udaipur district of Rajasthan. These 315 infertile cows were divided in three feed groups mainly balanced feed without mineral and vitamin mixture, balanced feed with vitaminised chelated mineral mixture and balanced feed with vitaminised chelated oxicareovn solution. These feed groups were treated with five therapy protocols viz. No hormone, Ovosynch(GPG48), Cosynch(GPG56), Cosynch+ progesterone (GPG56 + CIDR) and KVK-RDDC. The study revealed that the group 3 which fed balanced feed with vitaminised chelated oxicareovn solution have highest conception rate i.e. 61.0 % and followed by group 2 (Balanced feed with vitaminised chelated mineral mixture) and group 1 (Balanced feed i.e without mineral and vitamin mixture) viz. 44.8% and 29.5 %, respectively. On the basis hormone protocol, the animals which were treated with KVK-RDDC protocol have highest conception rate of 61.9 % and followed by GPG+CIDR (46.0%), GPG-56(46.0%), GPG-48(42.9%) and no hormone protocol (28.6%). On the basis of different managemental conditions, highest conception rate were of at commercial dairies i.e. 55.2% and followed by village animals (43.8%) and Gaushala’s (36.9%).

Reproductive abnormalities in women with a history of childhood diabetes are believed to be partially attributed to hyperglycemia. Prolonged hyperglycemia can negatively affect ovarian function and fertility during reproductive life. To address this in an experimental setting, the present study used streptozotocin-induced hyperglycemic prepubertal mouse model. The impact of prolonged hyperglycemic exposure during prepubertal life on ovarian function, oocyte quality, and functional competence was assessed in adult mice. The ovarian reserve was not significantly altered; however, the in vitro maturation potential (P < 0.001), mitochondrial integrity (P < 0.01), and meiotic spindle assembly (P < 0.05-0.001) in oocytes were significantly affected in hyperglycemic animals in comparison to control groups. The results from the study suggest that prepubertal hyperglycemia can have adverse effects on the oocyte functional competence and spindle integrity during the reproductive phase of life. Because these changes can have a significant impact on the genetic integrity and developmental potential of the embryos and fetus, the observation warrants further research both in experimental and clinical settings.

Sr(Al₀.₅Nb₀.₅)O₃ perovskite was synthesized via the solid-state reaction method and characterized to evaluate its suitability for solar cell applications. X-ray diffraction (XRD) analysis confirmed a well-crystallized cubic perovskite phase with an average lattice constant of 4.3810 Å. Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) revealed a nanostructured morphology with an average particle size of 33.54 nm, confirming the material’s high purity. Fourier Transform Infrared Spectroscopy (FTIR) identified characteristic metal-oxygen vibrational modes, ensuring proper perovskite phase formation. UV-Vis spectroscopy and Tauc plot analysis determined a direct bandgap of 1.54 eV and an indirect bandgap of 1.44 eV, making it a promising candidate for single-junction and tandem solar cells. The lead-free composition, strong UV absorption, and thermal stability of Sr(Al₀.₅Nb₀.₅)O₃ make it a potential material for next-generation photovoltaic applications.

The present study investigates the relationship between working capital management and SME profitability. It also analyzes the impact of macroeconomic impulses on firm profitability through efficient management of working capital in the case of Indian small and medium scale enterprises over the time period spanning from 2010 to 2017 using Feasible Generalized Least Square (FGLS) regression models. The study concludes the negative relationship of account receivables together with a positive relationship of inventories and account payables with SME profitability. It implies the firm managers can maximize SME’s profitability by converting the credit sales to cash as early as possible, by increasing the days of accounts payable and following a conservative inventory management strategy. Changes in economic growth and commercial bank advances to small scale industries are the key macroeconomic determinants that are impacting SME profitability. The results from this paper may guide the firm managers to shape their working capital management strategies to maximize profitability. Policymakers may find the study interesting to identify the macroeconomic parameters that significantly influence Indian SMEs.

The increasing demand for sustainable and efficient agricultural practices has accelerated the integration of artificial intelligence (AI), particularly deep learning, into modern farming systems. This study presents a comprehensive analysis of various deep learning classifiers—specifically CNN-based architectures—applied to key agricultural tasks, including crop classification, yield prediction, and harvest timing. Using both open-source and field-collected datasets encompassing image, climatic, and soil data, multiple models such as VGG16, ResNet50, InceptionV3, and a hybrid CNN+LSTM were evaluated for their effectiveness. The CNN+LSTM model consistently demonstrated superior performance, achieving the highest accuracy in classification and harvest timing, and the lowest error in yield estimation. These findings underscore the importance of combining spatial imagery with temporal environmental inputs for precision farming applications. The study also explores the practical relevance of deploying these models in real-world smart agriculture systems, while emphasizing future directions involving explainable AI, multimodal data fusion, and mobile-edge deployment for broader accessibility. Overall, this research contributes to the growing field of AI-driven agriculture by identifying robust, scalable models capable of enhancing decision-making processes across diverse agro-ecological settings.

Accelerated digitization has fundamentally reshaped how younger generations engage with brands and make purchasing decisions. As the first generation to grow up in a fully digital environment, Generation Z increasingly relies on social media platforms for product discovery, knowledge exchange, and identity creation. While literature on Gen Z consumer behavior is expanding, studies often examine drivers of purchase intention such as social media influence (Parker et al. 2019), identity-based consumption (Ogle 2020), or consumer values (Kumar &amp; Prakash 2021) in isolation. This study aims to develop a holistic conceptual framework for Gen Z purchase intention by integrating existing research on social media impact, digital selfconstrual, and consumer value orientations. Through a conceptual review, this paper synthesizes literature on digital marketing communication, symbolic consumption, and value-driven behavior. The findings indicate that Gen Z purchase intention cannot be fully explained by isolated factors. Instead, purchase motivations emerge from the interplay between digital communication environments, identity construction processes, and consumer value orientations (specifically materialism and consumer ethnocentrism). Consequently, this research proposes an alternative conceptualization of social media as a digital ecosystem that facilitates identity construction and consumption discourse, alongside consumer values that dynamically inform how individuals evaluate their choices. By linking digital marketing impact, identity-based consumption, and value-oriented decision making, this research contributes a more integrative perspective to the body of knowledge in consumer behavior. Ultimately, the framework extends the theoretical understanding of Generation Z purchase intention, particularly within fast-growing digital economies such as Indonesia.

In the present article, we have proved two common fixed point theorems (FPT) for complete metric space (CMS) with the help of upper semi-continuous function along with the existence and uniqueness of fixed point. These results are the generalizations of the well-known theorems Kannan fixed point theorem (KFPT) and Chatterjea fixed point theorem (CFPT) in the existed literature. The KFPT and CFPT are the generalizations of Banach fixed point theorem (BFPT).

This study evaluates the quality of dairy waste compost by assessing its effect on monocot and dicot seed germination using the tray method. Compost samples were mixed with soil in varying ratios, and germination rate, root, and shoot lengths of Vigna radiata (green gram) and Triticum aestivum (wheat) were recorded. The compost was produced using a Smartenviro Systems drum composter containing 40 kg of dairy sludge and 10 kg of sawdust as a bulking agent. Composting was carried out for 12–15 days at 45–55°C under thermophilic conditions, with daily drum rotation using a 0.5 HP geared motor for uniform aeration and mixing. The sawdust improved the C: N balance, enhancing organic matter degradation and yielding stable, odor-free compost. The automated, enclosed design minimized labor and leachate loss. Germination assays indicated that the compost-soil mixtures were non-phytotoxic and promoted early plant growth. Pathogen analysis confirmed the absence of Salmonella spp. and Staphylococcus aureus; however, detectable Escherichia coli and elevated chromium (Cr) levels above regulatory limits indicate incomplete sanitization and highlight the need for additional stabilization or post-treatment before unrestricted agricultural application. Overall, the results demonstrate the potential of controlled compost-soil blending for sustainable dairy waste management, while emphasizing the importance of further treatment to ensure microbiological and chemical safety.

Accelerated digitization has fundamentally reshaped how younger generations engage with brands and make purchasing decisions. As the first generation to grow up in a fully digital environment, Generation Z increasingly relies on social media platforms for product discovery, knowledge exchange, and identity creation. While literature on Gen Z consumer behavior is expanding, studies often examine drivers of purchase intention such as social media influence (Parker et al. 2019), identity-based consumption (Ogle 2020), or consumer values (Kumar & Prakash 2021) in isolation. This study aims to develop a holistic conceptual framework for Gen Z purchase intention by integrating existing research on social media impact, digital selfconstrual, and consumer value orientations. Through a conceptual review, this paper synthesizes literature on digital marketing communication, symbolic consumption, and value-driven behavior. The findings indicate that Gen Z purchase intention cannot be fully explained by isolated factors. Instead, purchase motivations emerge from the interplay between digital communication environments, identity construction processes, and consumer value orientations (specifically materialism and consumer ethnocentrism). Consequently, this research proposes an alternative conceptualization of social media as a digital ecosystem that facilitates identity construction and consumption discourse, alongside consumer values that dynamically inform how individuals evaluate their choices. By linking digital marketing impact, identity-based consumption, and value-oriented decision making, this research contributes a more integrative perspective to the body of knowledge in consumer behavior. Ultimately, the framework extends the theoretical understanding of Generation Z purchase intention, particularly within fast-growing digital economies such as Indonesia.

Accelerated digitization has fundamentally reshaped how younger generations engage with brands and make purchasing decisions. As the first generation to grow up in a fully digital environment, Generation Z increasingly relies on social media platforms for product discovery, knowledge exchange, and identity creation. While literature on Gen Z consumer behavior is expanding, studies often examine drivers of purchase intention such as social media influence (Parker et al. 2019), identity-based consumption (Ogle 2020), or consumer values (Kumar & Prakash 2021) in isolation. This study aims to develop a holistic conceptual framework for Gen Z purchase intention by integrating existing research on social media impact, digital selfconstrual, and consumer value orientations. Through a conceptual review, this paper synthesizes literature on digital marketing communication, symbolic consumption, and value-driven behavior. The findings indicate that Gen Z purchase intention cannot be fully explained by isolated factors. Instead, purchase motivations emerge from the interplay between digital communication environments, identity construction processes, and consumer value orientations (specifically materialism and consumer ethnocentrism). Consequently, this research proposes an alternative conceptualization of social media as a digital ecosystem that facilitates identity construction and consumption discourse, alongside consumer values that dynamically inform how individuals evaluate their choices. By linking digital marketing impact, identity-based consumption, and value-oriented decision making, this research contributes a more integrative perspective to the body of knowledge in consumer behavior. Ultimately, the framework extends the theoretical understanding of Generation Z purchase intention, particularly within fast-growing digital economies such as Indonesia.