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The purpose of this study is to reduce the application of petroleum in automobile paint industry by replacing it with bio-based castor oil along with nano fillers to synthesize automobile base coat (BC).

Bio-based polyurethane (PU) coating applicable in automobile BC was synthesized by using modified castor oil incorporated with nano silica (NS) and titanium-based pigment particles. The influential characteristics of the coating was studied by carrying out cross-cut tape test, abrasion resistance, pencil hardness, lap-shear, thermo gravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis and acid, alkali and oil resistance tests.

Incorporation of NS particles, along with titanium-based pigment particles in optimized ratio into the paint matrix, increases the mechanical, chemical and oil resistance properties and hydrophobicity of the BC, and the findings are compared with the petro-based commercial BC.

There is no significant improvement in thermal properties of the paint matrix, and it is less thermally stable than the commercial BC.

The paint developed through this study provides a simple and practical solution to reduce the petro-based feed-stock in automobile paint industry.

The current work which reports the use of ecofriendly PU BC for automobile paint applications is novel and findings of this study are original.

The purpose of this paper is to provide an analytical model for low carbon supplier development. This study is focused on the level of investment and collaboration decisions pertaining to emission reduction.

The authors’ model includes a fuzzy c-means (FCM) clustering algorithm and a fuzzy formal concept analysis. First, a set of suppliers were classified according to their carbon performances through the FCM clustering algorithm. Then, the fuzzy formal concepts were derived from a set of fuzzy formal contexts through an intersection-based method. These fuzzy formal concepts provide the relative level of investments and collaboration decisions for each identified supplier cluster. A case from the Indian renewable energy sector was used for illustration of the proposed analytical model.

The proposed model and case illustration may help manufacturing firms to collaborate with their suppliers for improving their carbon performances.

The study contributes to the low carbon supply chain management literature by identifying the decision criteria of investments toward low carbon supplier development. It also provides an analytical model of collaboration for low carbon supplier development. Though the purpose of the study is to illustrate the proposed analytical model, it would have been better if the model was empirically validated.

Though the earlier studies on green supplier development program evaluation have considered a set of criteria to decide whether or not to invest on suppliers, these are silent on the relative level of investment required for a given set of suppliers. This study aims to fulfill this gap by providing an analytical model that will help a manufacturing firm to invest and collaborate with its suppliers for improving their carbon performance.

Additive manufacturing has paved a way for geometrical freedom and mass customization of new and innovative products. However, it has a few limitations in printing complex geometries and sizes. The purpose of this paper is three-dimensional printing of metal parts using selective laser melting (SLM) has several intricacies.

To test the capabilities of SLM, the complex geometries of varying sizes, orientations, shapes such as square and cylindrical features, thin wall structures and holes were checked for dimensional accuracy and surface roughness.

The outcome of the study represents the capabilities of SLM and provide insight for solving the technological issues and processing constraint in the manufacture of metal parts from aluminum alloy. The analysis has proven that there is significant accuracy in dimension for large features in comparison with smaller one. The dimensional reproducibility was determined with the aid of an optical measuring system and the range of errors were calculated. These results show that the dimensional accuracy of the features in the printed part was within acceptable tolerance limits. This paper also investigated the significant contributing factors influencing printing of two and three-dimensional surface roughness based on the result of surface profilometer and it was observed that the surface was smoothened with the presence of overhangs and supports.

The ability of SLM to fabricate conformer cooling channels to support mould fabrication was tested. From the experimental result, it was observed that the quality of printing of conformal cooling channels depended on the diameter of channels with larger distortions in the channel having smaller diameter. The innovative aspect of the work was the study of build orientation combined with the investigated material.

This purpose of this paper was to conduct a study with an aim to reduce the cost of chicken nuggets by replacing part of lean meat with soy flakes. The suitability of chilled paneer whey was also assessed in place of ice water.

In the development of chicken nuggets, water-soaked soya flakes at the rate of 20 per cent were used in the formulation. The chilled whey at the rate of 8 per cent of the formulation was used to prevent the rise of temperature during emulsion preparation.

The product prepared in this way gave 5 per cent more yield than normal preparation in which ice water was used. The protein content in the preparation had gone significantly (p < 0.05) higher and moisture significantly (p < 0.05) lower than the normal control. The other proximate composition of chicken nuggets like fat and ash revealed no significant (p > 0.05) change in the product. Initially, thiobarbituric acid value and pH were observed lower in soya flakes-extended nuggets than the control. The overall acceptability was higher, that might be due to good binding and proper emulsion preparations.

Some experiments on amino acid profile and fatty acid profile are also required for further know-how about the actual nutritional status of chicken meat nuggets.

The products will be of immense value for the nutritional supplement and utilization of by-products like whey. It may also be a cost-effective formulation.

The products will be acceptable to all commodities because it is made up of chicken meat.

The cost of the formulation was also lower than the chicken nuggets used without soya flakes and whey because cost of meat was greater than the soya. The whey produced in paneer production costs less or by-product rich in protein materials can be better utilized into valuable products. The developed product seems to have great applications in the food industry and acceptability among consumers.

The purpose of the study is to perform elastic stress and deformation analysis of a functionally graded hollow disk under different conditions (rotation, gravity, internal pressure, temperature with variable heat generation) and their combinations.

The classical method of solution, Navier's equation, is used to solve the governing equation. The analysis considers thermal and mechanical boundary conditions and takes into account the variation of material properties according to a power law function of the radius of the disk and grading parameter.

The findings of the study reveal distinct trends and behaviors based on different grading parameters. The influence of gravity is found to be negligible, resulting in similar patterns to the pure rotation case. Variable heat generation introduces non-linear temperature profiles and higher displacements, with stress values influenced by grading parameters.

The study provides valuable insights into the behavior of displacement and stresses in hollow disks, offering a deeper understanding of their mechanical response under varying conditions. These insights can be useful in the design and analysis of functionally graded hollow disks in various engineering applications.

The originality and value of this study lies in the consideration of various loading combinations of rotation, gravity, internal pressure and temperature with variable heat generation. Furthermore, the study of effect of various angular rotations, temperatures and pressures expands the understanding of the mechanical behavior of such structures, contributing to the existing body of knowledge in the field.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

This paper aims to examine the impact of social capital and self-efficacy in the performance of producer organizations. It also tests the mediating influence of self-efficacy in the relationship of social capital and performance of producer organizations.

The study used data from a survey of 226 members of farmer producer organizations (FPO) in India. The model was tested through structural equation modeling wherein all hypotheses were tested using “R” studio.

The findings reveal that social capital and self-efficacy play a significant role in predicting the performance of FPO. It was found that in the process of social capital influencing the performance of FPO, self-efficacy plays a significant role as a partial mediator with a mediating effect of approximately 69.28%.

The study considered only one antecedent while identifying the reasons for perceived performance of FPOs. Hence, further studies of the various other constructs such as attitude, subjective norms, etc., may be considered.

No previous work has examined the mediating role of self-efficacy in the relationship between social capital and perceived performance of FPO. This study is possibly the only one that joins two streams of thought – social capital and self-efficacy – to examine the performance of FPO.

Tunnel field effect transistors (TFETs) have significantly steeper sub-threshold slope (24–30 mv/decade), as compared with the conventional metal–oxide–semiconductor field-effect transistors (MOSFETs), which have a sub-threshold slope of 60 mv/decade at room temperature. The steep sub-threshold slope of TFETs enables a much faster switching, making TFETs a better option than MOSFETs for low-voltage VLSI applications. The purpose of this paper is to present a novel hetero-junction TFET-based Schmitt triggers, which outperform the conventional complementary metal oxide semiconductor (CMOS) Schmitt triggers at low power supply voltage levels.

The conventional Schmitt trigger has been implemented with both MOSFETs and HTFETs for operation at a low-voltage level of 0.4 V and a target hysteresis width of 100 mV. Simulation results have indicated that the HTFET-based Schmitt trigger not only has significantly lower delays but also consumes lesser power as compared to the CMOS-based Schmitt trigger. The limitations of the conventional Schmitt trigger design have been analysed, and improved CMOS and CMOS–HTFET hybrid Schmitt trigger designs have been presented.

The conventional Schmitt trigger implemented with HTFETs has 99.9% lower propagation delay (29ps) and 41.2% lesser power requirement (4.7 nW) than the analogous CMOS Schmitt trigger, which has a delay of 36 ns and consumes 8 nW of power. An improved Schmitt trigger design has been proposed which has a transistor count of only six as compared to the eight transistors required in the conventional design. The proposed improved Schmitt trigger design, when implemented with only CMOS devices enable a reduction of power delay product (PDP) by 98.4% with respect to the CMOS conventional Schmitt trigger design. The proposed CMOS–HTFET hybrid Schmitt trigger further helps in decreasing the delay of the improved CMOS-only Schmitt trigger by 70% and PDP by 21%.

The unique advantage of very steep sub-threshold slope of HTFETs has been used to improve the performance of the conventional Schmitt trigger circuit. Novel CMOS-only and CMOS–HTFET hybrid improved Schmitt trigger designs have been proposed which requires lesser number of transistors (saving 70% chip area) for implementation and has significantly lower delays and power requirement than the conventional designs.