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Nanovaccinology and superbugs
Superbugs pose a serious threat to humans as many of the currently available antibiotics are not effective in treating the diseases inflicted by these microbes.Among the different bacteria causing clinical infections, Klebsiella pneumoniae, Escherichia coli, Serratia marcescens, Pseudomonas aeruginosa, Staphylococcusaureus, Proteus mirabilis, and so on, are some of the most vicious ones emergingat an unprecedented rate with huge impact on public health. In this context, prophylacticmeasures for these diseases assume great significance and NVs indeedfit in as a promising measure. Sustained release, improved antigen stability, betterimmunogenicity, better access to lymph nodes and low minimum immunotoxicitytranslates to the better efficacy of nano-based vaccines. Lipid-based NP (nanoparticles),dendrimers, Polymeric NP, self-assembled peptide NP, virus like particles(VLPs), and so on, are the promising NV (nanovaccines) delivery approaches.Improvisations of NVs by decorating NP surfaces with ligands that target specificimmune cells like the dendritic cells is also a promising approach to induce both Tand B cell responses. The current review focuses on the breakthroughs in the NVdomain with the challenges and opportunities of creating NVs to curb the menaceof superbugs. 2022 Scrivener Publishing LLC. All rights reserved. -
Comparative Analysis of Phytochemicals and Antioxidant Potential of Ethanol Leaf Extracts of Psidium guajava and Syzygium jambos
Background: Plant-based drugs for various human ailments are becoming very important in the current domain of therapeutics. Aim: Psidium guajava and Syzygium jambos are two such plant species known for their medicinal properties in traditional systems of medicine like Ayurveda. Methods: Phytochemical analysis including GCMS, and antioxidant studies (DPPH) was carried out for both plant extracts. Results: Comparative phytochemical analyses of ethanol extracts of both these plants have shown the existence of bioactive components like tannins, polyphenols, alkaloids, flavonoids and terpenoids. These phytochemicals were quantified and the ethanol extracts were subjected to GCMS analysis which showed the presence of cis-?-farnesene, cis-calamenene, copaene, humulene, caryophyllene, phytol, neophytadiene, n-hexadecanoic acid etc, many of which possess diverse properties like antimicrobial, antibiofilm, antioxidant and anti-inflammatory. DPPH and reducing power assays revealed the excellent radical scavenging activity of the extracts. Conclusion: Among the two plants under the current study, S. jambos extract showed better results when compared to P. guajava concerning the antioxidant potential and the quantity of flavonoids, alkaloids, polyphenols and tannins present in the plant samples. 2024, Informatics Publishing Limited. All rights reserved. -
Anti-biofilm activities of nanocomposites: Current scopes and limitations
The past few decades have seen revolutions in the applications of nanomaterials in different walks of science. One of the significant applications in healthcare is the use of nanoparticles (NP) in killing both free floating and biofilm forming bacteria. Several nanoparticles like CuO, Fe3O4, TiO2, ZnO, MgO and Al2O3 NPs have been proven to achieve this feature with varying efficacies. A more advanced and efficient way to disrupt bacterial biofilms is the use of nanocomposite (NC) materials to eliminate bacteria. Along with various metal oxides, materials like graphene and chitosan can also be used to create various types of NC. One of the biggest advantages of NP and NC over antibiotics is their ability to circumvent the problem of bacterial resistance. The mechanisms by which NC disrupts biofilms, synthesis and characterization of NC and their relative advantages and limitations are discussed in this chapter. With the ever-increasing incidences of diseases caused by multidrug resistant and biofilm forming bacteria, there is an urgent need to devise materials like nanocomposites with a broader spectrum of action. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Valorization of waste chilli stalks (Capsicum annuum) as a sustainable substrate for cellulose extraction: insights into its thermomechanical, film forming and biodegradation properties
Rising global population accelerates food waste generation, thereby creating a crisis in food waste management. A solution involves deriving value-added products like cellulose biopolymer from food waste. Chilli stalk wastes are one such food waste which are generated in large quantities and are unsuitable for field use or incineration due to health and environmental challenges. A greener alternative is extracting cellulose biopolymer from chilli stalk waste. The extraction of cellulose biopolymer from chilli stalk results in a renewable, biodegradable and economically efficient biomaterial with a broad range of applications. The extraction process involving alkali treatment (NaOH) and bleaching (alkaline H2O2), resulted in a yield of 29.85% cellulose biopolymer. The extracted cellulose was subjected to quantification and functional property analysis followed by characterization (FTIR, XRD, TGA, DSC and SEM) to analyse functional groups, crystallinity, thermal properties and surface morphology. Functional property analysis resulted in higher values when compared with commercial cellulose. The characterization techniques confirmed the effective removal of impurities such as lignin, hemicellulose and pectin by the chemical treatments. Cellulose sheets, fabricated using solvent casting, exhibited exceptional biodegradability (85.36%) within 20days, surpassing conventional food packaging materials, commercial food packaging paper (15.95 0.12% [%w/w]) and plastic sheets (7.89 0.33% [%w/w]) over the same time period. The novelty of this research lies in the innovative valorization of chilli stalk waste, which often remains unused in large quantities globally. This study introduces a cost-effective method to convert it into a value-added, highly biodegradable biopolymer. The resulting cellulose sheets provide an eco-friendly substitute for traditional food packaging materials. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Harnessing Wild Jackfruit Extract for Chitosan Production by Aspergillus versicolor AD07: Application in Antibacterial Biodegradable Sheets
A fungal strain with comparably high chitosan yield was isolated from the Shivaganga hills and identified as Aspergillus versicolor AD07 through molecular characterization. Later, the strain was cultivated on Sabouraud Dextrose Broth (SDB) and wild jackfruit-based media to evaluate its potential for chitosan production. Among the various media formulations, the highest chitosan yield (178.40 1.76 mg/L) was obtained from the jackfruit extract medium with added peptone and dextrose. The extracted chitosan was characterized through FTIR, XRD (reported a crystallinity index of 55%), TGA/DTG, and DSC analysis, confirming the presence of key functional groups and high thermal resistance. The extracted chitosan was fabricated into a sheet incorporated with 1% lemongrass oil; the sheet exhibited strong antibacterial activity against Escherichia coli (30 mm) and Bacillus megaterium (48 mm). The biodegradation studies reported a weight loss of 38.93 0.51% after 50 days of soil burial. Further, the chitosan film was tested as a packaging material for paneer, demonstrating better preservation by maintaining nutritional quality and reducing microbial load over a 14-day storage period. These findings highlight the potential of A. versicolor AD07-derived chitosan, cultivated on a waste substrate medium, as a sustainable biopolymer for food packaging applications. 2025 by the authors. -
Antibiofilm and anti-quorum properties of ethanolic leaf extracts of Syzygium jambos and Psidium guajava and their gel formulation for wound healing applications
Most bacterial species today have evolved with time and gained resistance to a wide range of antibiotics, primarily due to formation of biofilms and ?-lactamases. Many phytochemicals have been explored for their ability to inhibit bacterial biofilms. The present study sheds light on antibiofilm properties of two such plants viz. Psidium guajava and Syzygium jambos, of the Myrtaceae family. They were found to be effective against four different biofilm forming pathogens - Chromobacterium violaceum, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus. Synergistic use of the plant extracts showed slightly better antibacterial activity than a single extract. Quorum sensing being one of the key factors required for biofilm formation, the isolate Chromobacterium violaceum was used as the indicator organism to study the anti-quorum properties of the plant extracts. At 10 mg/mL, ethanolic extract of S. jambos inhibited violacein pigment the most (78.84%) and therefore can be considered as a quorum sensing inhibitor (QSI). Since silver nanoparticles (AgNPs) have become increasingly significant in the field of drug delivery, they may be utilized to coat implants to avoid subsequent infections in patients who have had implant surgery and to reduce biofilm development in pathogens. In the present study, five gels were formulated using plant extracts and AgNPs, of which two showed promising results in wound healing assay. The non-toxic nature of the synthesized gels has been verified by studies on L-929 mouse fibroblast cell lines, which opens the door for their prospective application as topical treatments to accelerate the healing process in both acute and chronic wounds. Given that S. aureus and P. aeruginosa are the most commonly isolated bacteria from diabetic foot ulcers, the resulting gels can considerably curb the spread of infection and gangrene and thus prevent amputation. Copyright: The Author(s) -
Bionanosensors in the Detection of Foodborne Microbial Pathogens
Food safety is of paramount importance especially in this era of extensive use of packaged and processed foods. The reasons for this are manifoldpathogens becoming more resilient and resistant and evolving at higher rates. The conventional ways of detection demands sophisticated instruments, time, trained personnel etc. Hence there is a dire need to devise user-friendly, highly sensitive and low-cost biosensors for foodborne microbial detection be it in fresh unprocessed plant products or processed food items. Nanobiosensors (NBS) owing to their high sensitivity, small size, very high surf to volume ratio which when combined with high accuracy optical imaging offer promising solutions to this global public health concern. The present review gives a glimpse of the latest technologies in the field of NBS in food borne microbial detection which includes graphene nanomaterials, quantum dot nanomaterials, metal nanoparticles and metal organic frameworks, carbon dots etc. The advantages of these NBSs, possible problems which can come up while upscaling the technique and its potential applications are also discussed. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Bionanosensors in the Detection of Foodborne Microbial Pathogens
Food safety is of paramount importance especially in this era of extensive use of packaged and processed foods. The reasons for this are manifoldpathogens becoming more resilient and resistant and evolving at higher rates. The conventional ways of detection demands sophisticated instruments, time, trained personnel etc. Hence there is a dire need to devise user-friendly, highly sensitive and low-cost biosensors for foodborne microbial detection be it in fresh unprocessed plant products or processed food items. Nanobiosensors (NBS) owing to their high sensitivity, small size, very high surf to volume ratio which when combined with high accuracy optical imaging offer promising solutions to this global public health concern. The present review gives a glimpse of the latest technologies in the field of NBS in food borne microbial detection which includes graphene nanomaterials, quantum dot nanomaterials, metal nanoparticles and metal organic frameworks, carbon dots etc. The advantages of these NBSs, possible problems which can come up while upscaling the technique and its potential applications are also discussed. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
FedDiff-Health: A Privacy-Preserving Generative Framework for Collaborative Hospital Readmission Prediction
Hospital readmission prediction encounters three challenges: data siloing across hospitals due to format incompatibilities, stringent privacy constraints, and the rarity of readmission events. We propose P-Fed-Diffusion, the first framework that enables collaboration across hospitals while keeping patients' data private. Our method automatically aligns heterogeneous data schemas without human intervention, using large language models. Then, we apply conditional diffusion models within a federated learning framework to generate synthetic data for rare readmission events. The framework incorporates formal privacy guarantees via differential privacy. We achieve a dramatic improvement over state-of-the-art methods: while the best prior method achieves 2% recall, we achieve 64% recall-32x improvement, meaning that the method finds over 1,000 additional high-risk patients per hospital annually. Our work opens up a new direction for privacy-preserving collaborative AI across hospitals. 2025 IEEE. -
Performance evaluation of Map-reduce jar pig hive and spark with machine learning using big data
Big data is the biggest challenges as we need huge processing power system and good algorithms to make a decision. We need Hadoop environment with pig hive, machine learning and hadoopecosystem components. The data comes from industries. Many devices around us and sensor, and from social media sites. According to McKinsey There will be a shortage of 15000000 big data professionals by the end of 2020. There are lots of technologies to solve the problem of big data Storage and processing. Such technologies are Apache Hadoop, Apache Spark, Apache Kafka, and many more. Here we analyse the processing speed for the 4GB data on cloudx lab with Hadoop mapreduce with varing mappers and reducers and with pig script and Hive querries and spark environment along with machine learning technology and from the results we can say that machine learning with Hadoop will enhance the processing performance along with with spark, and also we can say that spark is better than Hadoop mapreduce pig and hive, spark with hive and machine learning will be the best performance enhanced compared with pig and hive, Hadoop mapreduce jar. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. -
Big data performance evalution of map-reduce pig and hive
Big data is nothing but unstructured and structured data which is not possible to process by our traditional system its not only have the volume of data also velocity and verity of data, Processing means ( store and analyze for knowledge information to take decision), Every living, non living and each and every device generates tremendous amount of data every fraction of seconds, Hadoop is a software frame work to process big data to get knowledge out of stored data and enhance the business and solve the societal problems, Hadoop basically have two important components HDFS and Map Reduce HDFS for store and mapreduce to process. HDFS includes name node and data nodes for storage, Map-Reduce includes frame works of Job tracker and Task tracker. Whenever client request Hadoop to store name node responds with available free memory data nodes then client will write data to respective data nodes then replication factor of hadoop copies the blocks of data with other data nodes to overcome fault tolerance Name node stores the meta of data nodes. Replication is for back-up as hadoop HDFS uses commodity hardware for storage, also name node have back-up secondary name node as only point of failure the hadoop. Whenever clients want to process the data, client request the name node Job tracker then Name node communicate to Task tracker for task done. All the above components of hadoop are frame works on-top of OS for efficient utilization and manage the system recourses for big data processing. Big data processing performance is measured with bench marks programs in our research work we compared the processing i.e. execution time of bench mark program word count with Hadoop Map-Reduce python Jar code, PIG script and Hive query with same input file big.txt. and we can say that Hive is much faster than PIG and Map-reduce Python jar code Map-reduce execution time is 1m, 29sec Pig Execution time is 57 sec Hive execution time is 31 sec. BEIESP. -
Sustainability Indicators and Ten Smart Cities Review
The motivation of smart cities is to improve the standard of living of citizens and enhance the use of technology in sustainable city services. A city's sustainability can be measured using various sets of smart indicators. This study will analyse urban sustainability indicators as a research problem for ten smart cities. The review of smart cities will focus on the Internet of things (IoT), Mobile devices, and Artificial intelligence technologies (Sensors in street lights, smart homes) that help our citizens transform from rural to urban areas towards sustainability. This research uses a qualitative framework for the taxonomy of the literature for the terms 'smart city' and 'sustainability' Further, the characteristics, critical technology, and IOT application for mobility are elaborated upon. Finally, we discuss ten smart city review proposals reports, based on their sustainability indicators around the world. Concluding and Future studies could focus on using sustainable indicators for developing smart cities in India. 2023 IEEE. -
Role of Leadership and Management of Higher Education Institutions (HEI) in Digitalization
Throughout this chapter, several updated concepts, terms, and theoretical constructs are proposed about leadership and management of Higher Education Institutions (HEIs) with respect to the current trends and demands. The digital learning (DL) ecosystem and the transformational stages are discussed to elaborate the process of digital transformation at the HEIs. The advantages and benefits of digital education are integrated in the chapter with a view to better understand the challenges and opportunities brought forth by these imperatives. The chiseling role of leadership in the entire process is presented in the context of the digital ecosystem in order to meet the expectations of all the stakeholders. The New Education Policy (NEP) presents itself as a shaping force in accordance with prevailing standards and/or voluntary commitment by the respective HEIs in India. Further to the elaboration of the drivers of digitalization in the HEIs, the key takeaway is introduced as a holistic approach to leadership and management in such an ecosystem. 2024 Apple Academic Press, Inc. -
Predictive Analytics for Stock Price Forecasting: Machine Learning Techniques in Financial Markets
Stock market forecasting is significantly challenging because financial data generally exhibits non-linearity, and volatility is highly presented. Traditional methods such as the ARIMA model and NN fail to take a good grasp of intricate and complex temporal patterns in changes related to market trends. By overcoming these limitations, it makes use of LSTM and combines GAN networks. The LSTM exploits the historical stock price data for temporal dependencies, whereas GAN produces realistic synthetic data to augment model training. The Stock Market Dataset was used, and the proposed model was implemented using Python with TensorFlow and PyTorch frameworks. The hybrid LSTM-GAN model resulted in better performance with an RMSE of 0.0125, MAE of 0.0093, and R2 of 0.926, thus outperforming LSTM and traditional forecasting models. This work greatly enhances the accuracy of forecasting, avoids overfitting, and promotes performance in volatile market environments. The results are extremely useful for investors, financial analysts, and trading platforms because they can make better predictions. 2025 IEEE. -
The role of legal aid clinics in enhancing the employability, entrepreneurship and foundation skills for law students: A qualitative analysis
Access to justice is the basic postulate of a legal system. In this endeavour, universities have a unique institutional advantage to make a potential contribution to 100% access to justice by fostering a strong culture of social responsibility through innovative pro bono legal service initiatives and inculcating the professional value of legal service in the students and motivating them to develop a critical consciousness for social justice linked to the holistic development of law students. Consequently, the impact analysis of this training on global opportunities, both in terms of employability and higher education, formed the kernel of this chapter. Through in-depth interviews, focus group discussions and perspectives of researchers as participants in statelevel Legal services clinics, data was collected. Several key indicators were identified to analyze the expanded and holistic role of legal aid clinical education to effectively prepare students for their future. The study crystallizes a model for legal aid clinical courses by which Universities can deliver cutting-edge life and employability skills and enhance the professional competence of law students through direct participation in legal aid services. 2024 Nova Science Publishers, Inc. -
Research Advances on Foreign Portfolio Investments: A Bibliometric and Thematic Analysis
[No abstract available] -
Understanding learner adoption of generative AI-powered Ed-Tech applications by dissertation-based master students
Purpose This study aims to investigate the elements that influence master students' behavioral intentions to use generative artificial intelligence (AI) in educational contexts. It examines attitudes toward technology, effort expectancy and performance expectancy, with knowledge sharing as a mediating variable, to develop targeted interventions for enhancing the adoption of generative AI in Education Technology (Ed-Tech). Design/methodology/approach The study uses a stratified random sampling method. This sampling technique ensured that participants from various academic disciplines and dissertation themes were well-represented in the sample, thereby increasing data variety and representativeness. The population size was approximately 6, 034, and a sample of 392 participants was chosen for the study. The study employed a tripartite approach, utilizing IBM SPSS and AMOS to evaluate the validity and reliability of the investigated constructs. Structural equation modeling was then applied to test the proposed hypotheses. Findings The results emphasize the importance of Ed-Tech competencies, effort expectancy and performance expectancy in determining students' intent to use generative AI. Furthermore, the mediating role of knowledge sharing emphasizes its influence on technological adoption. Originality/value This study provides practical implications for academic institutions by informing tailored approaches to optimize student learning outcomes, dissertation progress and graduate employability. Through a comprehensive framework, it aims to promote inclusive technology access and create an environment conducive to maximizing the potential of generative AI-Ed-Tech in enhancing student success. 2026 Emerald Publishing Limited. -
An exploration of 'pull' and 'push' motivational factors among transgender entrepreneurs
To date, studies have focused on the men and women entrepreneurs and the gender difference in motivations among cisgender entrepreneurs. The study aims to determine whether a transgender individual entrepreneur is motivated through a push motivational factor or a pull motivational factor. This study employs a qualitative approach uses face-to-face interviews and a semi-structured interview with a sample size of 16 transgender entrepreneurs in India. It was found that the participants in this study were motivated by both push and pull factors. The motivational factors, which add to the knowledge of already existing push and pull factors, were to forego begging and commercial sex work, to break stereotypes, to create a business opportunity for other transgender individuals, to earn respect from society, to prove entrepreneurship is non-binary, to be a role model for other transgender individuals and to the society. In contrast, the push motivational factors were the limited opportunities, support received from society, the hijra guru, media, government support, family, friends, landlords, NGOs and another push motivational factor was the exhibitions conducted exclusively for the transgender individual entrepreneurs. 2025 Inderscience Enterprises Ltd. -
Entrepreneurial challenges of transgender entrepreneurs in India
Social exclusion has impeded transgender individuals to enter mainstream society and curbing them to start a business venture. Sporadic transgender individuals have paved their way to start the business venture. This study aims to explore the entrepreneurial challenges faced by transgender entrepreneurs. Twenty transgender entrepreneurs who have relinquished begging and commercial sex work were interviewed. The grounded theory analysis has revealed six significant categories: financial resources, competitors, human resources, marketing issues, natural calamities, and transphobia. The participants expressed that transphobia, and financial resources were highly challenging to start a business venture. These findings extend our understanding of their challenges beyond the current knowledge of cisgender entrepreneurs. Finally, the limitation of the study is enunciated. Copyright 2025 Inderscience Enterprises Ltd. -
An exploration of 'pull' and 'push' motivational factors among transgender entrepreneurs
To date, studies have focused on the men and women entrepreneurs and the gender difference in motivations among cisgender entrepreneurs. The study aims to determine whether a transgender individual entrepreneur is motivated through a push motivational factor or a pull motivational factor. This study employs a qualitative approach uses face-to-face interviews and a semi-structured interview with a sample size of 16 transgender entrepreneurs in India. It was found that the participants in this study were motivated by both push and pull factors. The motivational factors, which add to the knowledge of already existing push and pull factors, were to forego begging and commercial sex work, to break stereotypes, to create a business opportunity for other transgender individuals, to earn respect from society, to prove entrepreneurship is non-binary, to be a role model for other transgender individuals and to the society. In contrast, the push motivational factors were the limited opportunities, support received from society, the hijra guru, media, government support, family, friends, landlords, NGOs and another push motivational factor was the exhibitions conducted exclusively for the transgender individual entrepreneurs. 2025 Inderscience Enterprises Ltd.