Browsing by Author "Singh S"

Now showing 1 - 5 of 5

An innovative approach of progressive feedback via artificial neural networks
(2011) Singh S; Jokhan A; Sharma B; Lal S
Development of sustainable downstream processing for nutritional oil production
(Frontiers Media SA, 2023-10-10) Rollin S; Gupta A; Franco CMM; Singh S; Puri M; Sforza E
Nutritional oils (mainly omega-3 fatty acids) are receiving increased attention as critical supplementary compounds for the improvement and maintenance of human health and wellbeing. However, the predominant sources of these oils have historically shown numerous limitations relating to desirability and sustainability; hence the crucial focus is now on developing smarter, greener, and more environmentally favourable alternatives. This study was undertaken to consider and assess the numerous prevailing and emerging techniques implicated across the stages of fatty acid downstream processing. A structured and critical comparison of the major classes of disruption methodology (physical, chemical, thermal, and biological) is presented, with discussion and consideration of the viability of new extraction techniques. Owing to a greater desire for sustainable industrial practices, and a desperate need to make nutritional oils more available; great emphasis has been placed on the discovery and adoption of highly sought-after ‘green’ alternatives, which demonstrate improved efficiency and reduced toxicity compared to conventional practices. Based on these findings, this review also advocates new forays into application of novel nanomaterials in fatty acid separation to improve the sustainability of nutritional oil downstream processing. In summary, this review provides a detailed overview of the current and developing landscape of nutritional oil; and concludes that adoption and refinement of these sustainable alternatives could promptly allow for development of a more complete ‘green’ process for nutritional oil extraction; allowing us to better meet worldwide needs without costing the environment.
Integrated environmental process planning for the design and manufacture of automotive components
(Taylor & Francis, 2007) Singh S; Goodyer JE; Popplewell K
Advanced product quality planning (APQP) logic is widely used by manufacturers for the design and manufacture of automotive components. Manufacturers are increasingly finding difficulties to incorporate environmental considerations in the broad range of products that they manufacture. Therefore, there is a need for a systematic method for environmental process planning to evaluate product configurations and their associated environmental impact. The framework and models discussed in this paper can deal with a variety of product characteristics and environmental impacts through a selection of environmental performance indicators (EPIs) for a final product configuration. The framework and models have been applied in a real-life application and have proven that changes in product design or process selection can reduce the product's environmental impact and increase process efficiency. Hence, manufacturers can use the framework and models during the APQP process to benchmark each product variation that they manufacture in a standardized manner and realize cost saving opportunities.
Mutagenesis treatment of Mortierella alpina for PUFA production enhancement for future food development
(Elsevier B.V., 2025-06) Alhattab M; Lebeau J; Singh S; Puri M
Random mutagenesis has been identified as a key tool for improving microbial and fungal strains enabling the development of isolates with improved traits suited for industrial scale metabolite production to enhance the nutritional value of future foods. Presented here, is a random mutagenesis strategy employed to assess the effect of 5-fluorouracil (20-200 µg/ml), alone and in combination with the secondary agents octyl gallate and nocodazole, and diethyl sulfate (0.1 to 1 %) chemical mutagenic agents, on the biomass and lipid production as well as the FAME profile. Interestingly, a correlation was demonstrated between 5-fluorouracil exposure time and the arachidonic acid content, which was also influenced by the concentration used. 5-fluororuracil of 100 µg/ml treatment for 48 h resulted in the highest arachidonic acid (% TFA) content in isolates. Mutant M5F047 isolated with 5-fluororuracil (100 µg/ml) alone, proved to be most superior in terms of polyunsaturated fatty acid (PUFA) and arachidonic acid production, as compared to the Mortierella alpina wild type strain, with enhancements that doubled that of the parent strain. These improvements are more favorable for industrial scale production of arachidonic acid, a precursor of meaty flavour to improve plant-based meats in future food development.
Real and synthetic Punjabi speech datasets for automatic speech recognition
(Elsevier Inc, 2024-02) Singh S; Hou F; Wang R
Automatic speech recognition (ASR) has been an active area of research. Training with large annotated datasets is the key to the development of robust ASR systems. However, most available datasets are focused on high-resource languages like English, leaving a significant gap for low-resource languages. Among these languages is Punjabi, despite its large number of speakers, Punjabi lacks high-quality annotated datasets for accurate speech recognition. To address this gap, we introduce three labeled Punjabi speech datasets: Punjabi Speech (real speech dataset) and Google-synth/CMU-synth (synthesized speech datasets). The Punjabi Speech dataset consists of read speech recordings captured in various environments, including both studio and open settings. In addition, the Google-synth dataset is synthesized using Google's Punjabi text-to-speech cloud services. Furthermore, the CMU-synth dataset is created using the Clustergen model available in the Festival speech synthesis system developed by CMU. These datasets aim to facilitate the development of accurate Punjabi speech recognition systems, bridging the resource gap for this important language.