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This study explored the combined administration of docetaxel (DOC) and erlotinib (ERL) using nanostructured lipid carriers (NLCs), with folic acid (FA) conjugation to enhance their synergistic anticancer efficacy against triple-negative breast cancer. NLCs were developed through hot melt homogenization–ultrasound dispersion, and optimized by a quality-by-design (QbD) approach using Plackett–Burman design and Box–Behnken design. Plots were generated based on maximum desirability. Spherical, nanosized dispersions (<200 nm) with zeta potential ranging from −16.4 to −14.15 mV were observed. These nanoformulations demonstrated ~95% entrapment efficiency with around 5% drug loading. Stability tests revealed that the NLCs remained stable for 6 months under storage conditions at 4 °C. In vitro release studies indicated sustained release over 24 h, following Higuchi and Korsmeyer–Peppas models for NLCs and FA NLCs, respectively. Additionally, an in vitro pH-stat lipolysis model exhibited a nearly fivefold increase in bioaccessibility compared to drug-loaded suspensions. The DOC–ERL-loaded formulations exhibited dose- and time-dependent cytotoxicity, revealing synergism at a 1:3 molar ratio in MDA-MB-231 and 4T1 cells, with combination indices of 0.35 and 0.37, respectively. Co-treatment with DOC–ERL-loaded FA NLCs demonstrated synergistic anticancer effects in various in vitro assays. [ABSTRACT FROM AUTHOR]

Purpose: The global organic market is expanding, and India is in an advantageous position with the highest number of organic producers worldwide. Although many articles have been published on the value chain of organic products from India, no significant studies were found related to the value chain analysis of organic pineapple. This study aims to know the various aspects of the organic pineapple value chain, i.e. network structure, value addition at various stages of chain actors, value chain upgradation and governance structure. Design/methodology/approach: The study is explorative in nature, and primary data from various actors involved in the chain is collected and analyzed. Primary data through a structured schedule and interviews are collected from farmers and traders. A multistage sampling plan has been adopted. A sample of 75 farmers was randomly selected from the study area. For traders, snowball sampling is used due to the nonavailability of the sampling frame. A total of 10 commission agents, 10 wholesalers and 20 retailers were thus selected for the study. For objectives 1 and 4, descriptive statistics are used. For objective 2, a modified formula described by (Murthy et al., 2007) is used to calculate farmer's net price and marketing margin. For objective 3, Garrett's ranking technique is used to identify various constraints in upgrading the organic pineapple value chain in Assam. Findings: This study shows that the value chain of organic pineapple is in the initial stage and proper value addition is required to have a complete regulated value chain. Six marketing channel is identified, and products are sold through farmer producer company only in case of export and trade with distant buyers. The marketing efficiency for channels II and III is 1.69 and 0.99, respectively. The degree of value addition for channel II in the hands of the commission agent, wholesaler and retailer is 11.65%, 4.56% and 12.60%, respectively. In the various constraints in upgrading the value chain, farmers rank "policy support" as a major constraint. In the governance structure, trade with distant traders and exports is done formally and through written contracts. Research limitations/implications: The study performs value chain analysis of organic pineapple in Cachar district of Assam, India for the year January 2022–January 2023. Future studies are encouraged related to various aspects of the supply chain and value chain of organic pineapple from various northeastern states of India and other states. Practical implications: The study will help policymakers and key actors to know the existing chain and frame a well-coordinated and regulated value chain. Originality/value: This study is one of the first study to explore the value chain of organic pineapple of Cachar district of Assam, India. Implementation of these findings can help various actors to strengthen the existing value chain. [ABSTRACT FROM AUTHOR]

Aim: This work aims to synthesize the gold nanoparticles (GNPs) using a dual extract of tulsi and Vinca (T+V-Gold) for breast cancer tumor regression. Methods: The GNPs were synthesized and characterized for their microscopic, spectroscopic and crystalline properties. Further, the GNPs were investigated for in vitro and in vivo studies for the treatment of the 4T1-induced triple-negative breast cancer murine model. Results: The GNPs for 4T1 tumor-challenged mice resulted in delayed tumor development and lower tumor burden, with T+V-Gold demonstrating the highest prevention of tumor spread. The antitumor effect of T+V-Gold is highly significant in the glutathione family antioxidants glutathione S-transferase and glutathione in tumor tissue samples. Conclusion: The bioefficacy and anticancer outcomes of T+V-Gold nanoformulation can be used as therapeutic agents and drug-delivery vehicles. [ABSTRACT FROM AUTHOR]

The darker side of food behavior is that millions of tons of food have been shown the doors of garbage. Therefore, food waste behavior needs an eye to look upon. The purpose of this research is to inculcate the concept of systematic literature review along with meta-analysis in order to examine the Theory of Planned Behavior (TPB) with respect to food waste behavior. The methodology includes Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) that is conducted for the identification, screening, and inclusion of studies. In all, twenty-six independent studies with (N = 13373) met the inclusion criteria. For validating the related literature, random-effects meta-analysis has been applied for ascertaining the average correlation among the variables. More specifically, the present study also examines the sub-group analysis effect among TPB variables. The findings reveal that the strongest association was observed between Attitude and Intention followed by Subjective Norm (SN) and Intention (INT), Perceived Behavioral Control (PBC) and Intention, and Intention and Behavior. Furthermore, the subgroup analysis using multi-cultural groups explores the highest composite correlation in the case of other cultural groups that included countries like Canada. The outcomes of the present study seek to serve in the best interest of households, event management stakeholders, and food policy makers. [ABSTRACT FROM AUTHOR]

Zinc oxide nanoparticles (ZnO NPs) are one of the most abundant metal oxides nanoparticles. It provides excellent thermal, electrical and chemical stabilities with low biotoxicity; its photo-oxidising and photo-catalytic impact on biological and chemical species is of great importance, thereby making it a promising candidate to be used for in vitro and in vivo studies in biomedical field. Hereby, ZnO NPs were synthesized using precipitation method with zinc acetate and sodium hydroxide as starting materials. This study has characterized the synthesized ZnO NPs using different techniques such as UV-Visible spectroscopy indicating a peak at 365 nm wavelength, size of ZnO NPs was determined to be 286.7 nm by measuring hydrodynamic radii using Dynamic Light Scattering (DLS) phenomena. Further predominant charge existing at surface of the synthesised ZnO NPs was evaluated to be 31.6 mV. Anti-microbial activity of ZnO NPs was determined by Kirby-Bauer method for both Gram-positive and Gram-negative bacteria, S. aureus and E. coli, respectively. Anti-microbial activity was determined as Zone of Inhibition that measures both bactericidal and bacteriostatic activity of ZnO NPs and was found to be more potent for Gram-positive (S. aureus) bacteria and its activity increased with increasing concentration of nanoparticles. Growth kinetics was studied to determine percentage growth inhibition, for this optical density was recorded as a function of time in bacterial culture broth with and without treatment. Further DNA fragmentation assay was performed to determine genotoxicity caused by nanoparticles and its effect on genomic DNA of bacteria. Highlighting its potential role as a nano-carrier system for leading antibacterial drugs for enhanced effectiveness of the antibacterial therapies. [ABSTRACT FROM AUTHOR]

Supply Chain Collaboration (SCC) has been a topic of great interest among the supply chain researchers for decades now. Collaboration among channel-partners is imperative for successful supply chain management and may be the most critical core competency for enhancing the supply chain performance. This paper examines the various SCC frameworks and their development through a bibliometric analysis of the SCC literature published under the Web of Science (WoS) database in the last twenty years from 2003 to 2022 (including early access for January, 2023) comprising of 4249 research articles. The analysis and graphical visualization of the bibliometric data is presented using measures of descriptive statistics and visualization tools identifying the linkages between the published literature. This study analyses the distribution of the publications based on the research author analysis, most cited publications analysis, publication source analysis, country-wise literature analysis and the keywords co-occurrence analysis. The study also examines the most cited researches on SCC in last two decades and attempts to collate the major developments in the SCC knowledgebase. This research corroborates the enormity of the research conducted in the past and accentuates the ever-growing significance of collaboration in the supply chains for future researchers and businesses worldwide. On an average more than two hundred articles are published every year on SCC and the time-series forecasts reaffirm its progressiveness and relevance as a research domain more than ever engaging researchers and business organisation across the globe. The systematically collated data of top twenty most cited articles, authors, journals, keyword and countries involved in SCC research has been prepared which will provide a source of practical reference for the early supply chain researchers and professionals globally. [ABSTRACT FROM AUTHOR]

With the rapid advancements of the internet of things (IoT), several applications have evolved with completely dissimilar structures and requirements. However, the fifth generation of mobile cellular networks (5G) is unable to successfully support the dissimilar structures and requirements. The sixth generation of mobile cellular networks (6G) is likely to enable new and unidentified applications with varying requirements. Therefore, 6G not only provides 10 to 100 times the speed of 5G, but 6G can also provide dynamic services for advanced IoT applications. However, providing security to 6G networks is still a significant problem. Therefore, in this paper, a hybrid image encryption technique is proposed to secure multimedia data communication over 6G networks. Initially, multimedia data are encrypted by using the proposed model. Thereafter, the encrypted data are then transferred over the 6G networks. Extensive experiments are conducted by using various attacks and security measures. A comparative analysis reveals that the proposed model achieves remarkably good performance as compared to the existing encryption techniques. [ABSTRACT FROM AUTHOR]

Over the course of the food supply chain, approximately one-quarter of the food produced for human consumption is thrown away. According to the World Food Waste Survey, food waste created at the household level accounts for almost half of the total food waste. A growing number of people are becoming concerned about food security and environmental consequences, such as resource depletion and greenhouse gas emissions associated with food waste. This has heightened public awareness of the issue. Despite the fact that food waste happens at every level of the food supply chain, private households have been recognized as being the primary source of food waste production. However, there is currently a lack of studies about the factors that influence consumer food waste behavior. This paper presents a twofold study. In the first section, this paper maps drivers of food waste at household level along with the remedies backed by extensive literature review. In the second section, this study identifies factors which are responsible for food waste in social gathering with special reference to weddings along with solutions to prevent food waste in the context to social gathering through systematically reviewing empirical studies on food waste practices. The results of the study demonstrate that food waste is a complex and multi-faceted issue that cannot be reduced to a single variable; as a result, a more comprehensive integration of multiple academic viewpoints is required. The mapping of the factors of waste creation allows for a more in-depth knowledge of household habits, party organizers' practices, guest behaviors toward food, and the development of food waste control policies. Finally, we connect the factors that have been found with formulation of policy, business, and social responsibilities. This study will be a value addition in the existing pool of literature concerned with responsible consumption and sustainable practices. [ABSTRACT FROM AUTHOR]

Structural, magnetic, and transport properties of Ni52+xMn26-xAl22 (1 ≤ x ≤ 5) melt-spun ribbons have been characterized by a variety of experimental techniques. As the composition changed from x = 1 to x = 5, the martensitic transition temperature T0 [ = (Ms + Af)/2] was found to increase from 277 K to 446 K which was attributed to an increase in the valence electron concentration e/a. In the martensitic state, all the samples demonstrate an anomalous semiconducting behavior of electrical resistivity ρ. This uncommon feature of the transport properties has been ascribed to the existence of a gap (Eg ∼ 0.1 eV) at the Fermi level. A crossover from semiconducting to metallic behavior of ρ observed in the martensitic state of Ni57Mn21Al22 is presumably related to a spin-density wave formation at the Neel temperature TN ≈ 300 K. Analysis of a low-temperature (T < 60 K) part of the resistivity curves and comprehensive magnetic measurements of a Ni57Mn21Al22 (x ≤ 5) sample provide grounds for the conclusion that the splitting of zero-field cooling and field cooling magnetization curves observed at low temperatures is due to a spin-glass state that is formed below the freezing temperature Tf. [ABSTRACT FROM AUTHOR]

The extensively researched and refined relationship between service quality and customer loyalty has found recognition under a wide variety of colloquiums and contexts. Service quality is conspicuous for its eminence in customer loyalty formulation in marketing literature rich with both relevant theoretical and empirical evidences (Boulding et al., 1993; Parasuraman et al., 1991; Zeithaml et al., 1996). Studies have primarily investigated and established its impact over various dimensions of loyalty manifesting into repurchases, revisits, recommendations, etc. However, investigations into the association of service quality with individual dimensions of customer loyalty and the probable interaction effects affecting the shape or strength of such associations are clearly sparse. The present paper aims at exploring and establishing the link between service quality and a two dimensional model of customer loyalty with reference to the life insurance industry in India. Further, it intends to review the relationship of customer loyalty with its prominent precursors - trust and customer satisfaction with a new perspective. A conceptual research proposition encompassing the effect of service quality on attitudinal and behavioral dimensions of customer loyalty along with the potential interaction effects of trust and customer satisfaction in these relationships has been tested and presented by the study with intent to bring in fresh propositions and perspectives. The findings support the presence of these effects and call for approaching the goal of customer loyalty development with due consideration to the desired outcomes and the conditions required for cultivating them. [ABSTRACT FROM AUTHOR]

Results of fundamental and third order ac susceptibility measurements in a Ni49Mn29Ga22 single crystal demonstrate that higher harmonics of ac-susceptibility measurement is an excellent tool to identify transitions/anomalies originating from different magnetic substructures that remain undetected by usual dc susceptibility measurements. Anomaly observed at low temperature (∼150 K) has also been explored by differential scanning calorimetry, temperature dependent x-ray diffraction, and transmission electron microscopy measurements. The results demonstrate that the magnetic subsystem in Ni-Mn-Ga is unstable at low temperatures not only for metastable modulated crystal structure but also for very stable nonmodulated tetragonal structure. [ABSTRACT FROM AUTHOR]

Magnetic and structural properties of Ni–Mn–Al thin films are investigated. It is demonstrated that the annealed film shows L21 phase at room temperature. Magnetometry measurements reveal that the annealed film is ferromagnetic and a first order transition in magnetization versus temperature measurement confirms that the martensite to austenite transition occurs around room temperature. Transmission electron microscopy measurements confirm that this structural change occurs just below room temperature. The splitting of Mn 2p3/2 level in x-ray photoelectron spectroscopy core level spectra of the annealed Ni–Mn–Al film, confirms that the origin of magnetism is definitely correlated with the local magnetic moment at the Mn atoms. [ABSTRACT FROM AUTHOR]

A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy because the text classification systems lack the ability to model the input text data in terms of noise characteristics. This research study proposes a concept of misrepresentation ratio (MRR) on input healthcare text data and models the PE criteria for validating the hypothesis. Further, such a novel system provides a platform to amalgamate several attributes of the ML system such as: data size, classifier type, partitioning protocol and percentage MRR. Our comprehensive data analysis consisted of five types of text data sets (TwitterA, WebKB4, Disease, Reuters (R8), and SMS); five kinds of classifiers (support vector machine with linear kernel (SVM-L), MLP-based neural network, AdaBoost, stochastic gradient descent and decision tree); and five types of training protocols (K2, K4, K5, K10 and JK). Using the decreasing order of MRR, our ML system demonstrates the mean classification accuracies as: 70.13 ± 0.15%, 87.34 ± 0.06%, 93.73 ± 0.03%, 94.45 ± 0.03% and 97.83 ± 0.01%, respectively, using all the classifiers and protocols. The corresponding AUC is 0.98 for SMS data using Multi-Layer Perceptron (MLP) based neural network. All the classifiers, the best accuracy of 91.84 ± 0.04% is shown to be of MLP-based neural network and this is 6% better over previously published. Further we observed that as MRR decreases, the system robustness increases and validated by standard deviations. The overall text system accuracy using all data types, classifiers, protocols is 89%, thereby showing the entire ML system to be novel, robust and unique. The system is also tested for stability and reliability. [ABSTRACT FROM AUTHOR]