Devi Ahilya Vishwavidyalaya

In a practice of art work, particularly while painting, an artist seems to bring about visual depth of certain areas of the painting with help of changing or altering hue using tints, shades, and tones of different colours. Here, in this paper I have discussed a property of a pair of colours causing Chromostereopsis, that is, a visual effect of certain pair of colours where one colour is seen ahead of the other colour even though they are on a two-dimension surface. At the same time, I have discussed the possibility of enhancement of depth when these colours are applied over a textured surface created with help of Impasto.I have used experiments to access the hypothesis, where I conducted three experiments; one each for showing the known Chromostereopsis with complimentary colours, second using same pair of colours over a textured surface created with help of Impasto (thick paste) of white and grey colours. I conducted the third experiment by reversing the places of the two colours of the pair that was used earlier. Some amazing results were found, which have been noted and discussed in the discussionThe hypothesis was established both by reading on internet about Chromostereopsis and Impasto and with findings from my experiments.

Hyperspectral remote sensing (HRS) image classification is time-consuming and complex due to its wide spectral range and large number of samples. Factors such as heterogeneous behaviour, unbalanced class distributions, complex boundaries, multiple spectral bands, inconsistent samples, significant spatial variability, and interclass similarities further challenge image classification. The design of a robust classification model that addresses these challenges demands efficient pre-processing of input information, e.g., dimensionality reduction and representative feature extraction, with the ability to handle information uncertainty and to reduce computational complexity. In line with these objectives, we have proposed a classification model called FRELM-SAE, which utilises fuzzy granulation of input features, a rule-based extreme learning machine (ELM), and a stacked autoencoder (SAE). Fuzzy granulation and rule-based ELM address the generalisation aspects and the complexity of the decision-making process. The SAE reduces the noise from the input feature space and performs representative feature extraction. Various experiments demonstrate the proposed model’s performance in classifying two HRS images. The experimental results show its supremacy over related work across performance metrics, including overall accuracy, precision, recall, etc.

Abstract In this study we characterized a protease extracted from the mucilage and fat-free seeds of Ocimum basilicum . The purification process involved ammonium sulfate precipitation followed by ion exchange chromatography. The molecular weight of purified enzyme, as determined by SDS-PAGE was found to be 60.5 kDa. This protease was identified as a serine protease, as its activity was inhibited by phenylmethylsulfonyl fluoride (PMSF) and aprotinin. Cleavage of azo-casein indicates it to be endoprotease. The enzyme exhibited a maximum reaction velocity (Vmax) of 0.066 mM/min and a Michaelis constant (Km) of 0.53 mM using BAPNA as a substrate. The optimal pH for enzyme activity was found to be 5, and the optimal temperature was determined to be 40°C. The activation energy was measured at 3.82 kcal/mol, with an enthalpy change of 2.16 kcal/mol and a Q 10 value of 1.20. The protease demonstrated stability within a pH range of 3 to 7 and at temperatures from 4 to 50°C. Notably, exposure to microwaves increased its proteolytic activity by 56%. Among the metal ions investigated, Fe³⁺ was identified as an effective competitive inhibitor. Additionally, this protease showed significant effectiveness in removing blood stains when combined with sodium dodecyl sulfate (SDS) and was also able to clot milk. This research represents the first characterization of a protease from Ocimum basilicum seeds, highlighting its potential applications in the detergent industry and food production, particularly in cheese making.

Purpose : The purpose of this study was to investigate the relationship between knowledge management (KM) and organizational performance (OP) through employee job satisfaction (JS). If knowledge management has an impact on JS and subsequently OP, then organizations can develop KM systems that will allow them to develop strategies to improve their overall performance. Methods : A structural equation modeling (SEM) methodology was employed using a sample of 190 staff from the hospitality industry in Madhya Pradesh, India, to investigate the relationship between KM and OP with a focus on JS as a mediator. Results and Findings : The results and findings provided strong evidence for the positive impact of KM on OP, as well as JS, as having a substantial role in mediating the relationship between KM and OP. Practical Implications : The results bring out the meaningfulness of designing and executing KM practices to strengthen job fulfilment and hence organizational productivity. As such, organizations providing hospitality services should recognize the role of KM and utilize it as a means to buildup organizational outcomes; furthermore, by focusing more on improving JS as a result/outcome of KM, organizations might be able to additionally strengthen the positive impact of KM on OP/productivity. Originality : The KM practices used in the study are regarded as novel compared to those referenced in previous literature. The distinctiveness of this study thus adds value to the existing literature in providing new perspectives into how organizations can improve their performance through improved KM practices.

The objective of this study is to investigate the equilibrium thermodynamic and structural properties of small proteins in the presence of an implicit solvent using the SMMP package. The work primarily focuses on performing parallel tempering simulations for the peptides Met-enkephalin. The thermodynamic parameters, such as specific heat and average energy, structural properties like radius of gyration and end to end distance with respect to temperature were calculated as functions of temperature to analyze the stability and Conformational behavior of the proteins.