Eigenvalues Research Articles

Genetic diversity among maize (Zea mays) inbred lines for methionine and yield associated traits

A study was carried out during winter (rabi) and rainy (kharif) seasons of 2020–21 at the research farm of ICAR-Indian Institute of Maize Research, Ludhiana, Punjab in which 22 maize inbred lines with varying content of methionine were evaluated to study various seeds and field parameters, and methionine content and further statistically analysed through genetic variability, principal components and hierarchical cluster analysis. Significant differences were noted among inbred lines for various traits. Broad- sense heritability analysis showed that traits exhibited more than 80% heritability, except plant height, cob height and no. of cobs. Principal component analysis showed five principal components having eigen value more than 1.00 and accounted for 82.01% of total variation. Cluster analysis distributed the inbred lines in 4 major clusters suggesting their use in breeding programmes. Correlation analysis was also studied to understand the correlation of field and yield parameters with methionine content. Plant height and cob height (0.83), no. of rows per cob and no. of seeds per row (0.76), anthesis and silking interval (0.89), specific gravity and silking interval (0.45) showed significant positive correlation. Traits including methionine, moisture, 100-kernel weight, no. of cobs, no. of rows/cob, no. of seeds/row and germination rate having higher genotypic and phenotypic coefficient of variation, heritability, and genetic advance mean can be used for further crop improvement programme.

Traveling wave solution and the stability of critical points of an enzyme-inhibitor system under diffusion effects: with special reference to dimer molecule

Enzymes are absolutely essential biological catalysts in human body that catalyze all cellular processes in physiological network. However, there are certain low molecular weight chemical compounds known as inhibitors, that reduce or completely inhibit the enzyme catalytic activity. Mathematical modeling plays a key role in the control and stability of metabolic enzyme inhibition. Enzyme stability is an important issue for protein engineers, because of its great importance and impact on optimal utility of material in biological tissues. In this outlook, we have first determined the existence of traveling wave solution for the enzyme-inhibitor system and then emphasized the stability of critical points that arise in the reactions. The study of traveling wave solution of an enzyme-inhibitor system with reaction diffusion equations involve quite complex mathematical analysis. The results obtained in this model indicate that the traveling wave solution may give a well explained method for improving enzyme kinetic stability. The present study will be helpful in understanding the stability of critical points of an enzyme-inhibitor system to give an idea about the inhibition of less stable enzymes. Moreover, the role of diffusion on the enzyme activity has been exhaustively discussed using mathematical tools related to eigen values and eigen function analysis.

Facial Recognition Attendance Monitoring System using Deep Learning Techniques

The Facial Recognition Attendance Monitoring System employing Deep Learning Techniques represents a cutting-edge application of artificial intelligence in educational and corporate environments. The implementation of a Facial Recognition System can aid in identifying or verifying a person's identity from a digital image. Accurate attendance records are vital to classroom evaluation. However, manual attendance tracking can result in errors, missed students, or duplicate entries. The adoption of the Face Recognition-based attendance system could help eliminate these shortcomings. This innovative approach involves utilizing a camera to capture input images, detecting faces using algorithms such as Haarcascade, Eigen values, support vector machines, or the Fisher face algorithm, verifying the faces against a database of student profiles, and marking attendance in an Excel sheet. The use of OpenCV, an open-source computer vision library, ensures the efficient

Evaluation of the Applicability of Digital Photogrammetry-Based Initial Imperfections on NLFEM Ultimate Strength Analysis of Ship- Type Stiffened Plates

In this study, the effects of initial imperfections on the ultimate strength values of ship-type stiffened plate structures are discussed and analysed from the point of view of how the initial imperfection forms are obtained. Ship stiffened panels are subjected to complex loading conditions during their operational lifespan. Accurate prediction of their strength and failure modes necessitates a thorough understanding of the effects of various imperfections on their behavior. Two primary sources of initial imperfections are considered: the buckling mode shapes resulting from linear eigenvalue buckling analysis and measurements based on digital photogrammetry. Buckling mode shapes, arising from the manufacturing process are extracted using linear static structural analysis. Digital photogrammetry is employed to capture and quantify imperfections by analysing high-resolution images of the physical structure. Numerical investigation is conducted by incorporating these two types of initial imperfections into non-linear finite element method (NLFEM) calculations. The buckling mode imperfections are applied as geometric perturbations, while the photogrammetry-based imperfections are incorporated as statistically representative deviations from the ideal geometry. Stiffened panel's structural response is analysed under longitudinal uniaxial compression. A new NLFEM project schematic has been utilized instead of the procedure outlined in the technical circular S.P 01/19 by Türk Loydu, which has been discontinued after ANSYS® Workbench™V.2019R2. This is proven by two validation case studies in ANSYS® Workbench™2022R2 version for considering buckling mode initial imperfections. A case study is then conducted using a 3D model of a stiffened plate panel, which is fabricated in a shipyard located in Trabzon, created by Photomodeler V. 2023.3.0.238 employing the digital photogrammetry method.NLFEM analysis is carried out for both initially deflected model after eigenvalue buckling analysis and naturally deflected model after welding operations. The comparative ultimate strength results are quite consistent, and this shows that the digital photogrammetric modelling method can be used in the analysis of ship structural elements.

Principal Component Analysis of Grain Yield and its Attributing Traits in Recombinant Inbred Lines of Rice (Oryza sativa L.) Developed for Submergence Tolerance

Submergence is an important abiotic stress affecting yield and productivity of rice. There are many landraces such as AC 42088, AC 42087 and AC 38575 which show tolerance to long duration flooding. These landraces can be used as donors in breeding programs for development of improved varieties which show increased yield as well as tolerance to submergence. To study the variability in yield and its attributing traits in the population, principal component analysis was carried out. The present investigation was studied in recombinant inbred lines (RIL) population consisting of 120 lines where principal component analysis was carried out on different agromorphological traits viz. days to fifty percent flowering, plant height, panicle length, total tillers per plant, number of effective tillers per plant, number of filled grains and Spikelet fertility, test weight, grain yield per plant, biomass per plant and harvest index to assess the relative contribution of various traits towards total variability. It was found that first five components with Eigen values greater than 1 accounted for 74.33% of total explained variability. The highest positive eigenvalue was observed for plant height and panicle length in PC1, revealing their maximum contribution to variation in the lines.

Development of Nursing Students Stressor Questionnaire

Background: Stress has become a chronic and pervasive condition in the world today. Any stimulus which evokesa stress response is called a stressor. The objective of the study was to develop a questionnaire to measure stressorsamong first year B.Sc nursing students in Kerala.Methods: Descriptive cross sectional design integrating both qualitative and quantitative methods were used forthe study. Data was analyzed by qualitative content analysis, descriptive and inferential statistics.Results: A 22 item screening instrument named as Nursing Students Stressor Questionnaire (NSSQ) was developed.Test retest reliability was found to be 0.923 with 95% CI 0.878 – 0.957. The internal consistency Cronbach’s alpha ofthe tool was 0.866. Construct validity was established by exploratory factor analysis which yielded seven factorswith Eigen Values more than one. The factors explained 60% of total variance.Conclusion: NSSQ is a simple, easy to administer, self-reported screening instrument with acceptable reliabilityand validity.

Genetic diversity, morphological traits, quality traits and antioxidants potentiality of Coccinia grandis germplasm under rainfed semi-arid region

The present study was conducted to evaluate the genetic variability for morphological and qualitative traits of Coccinia for development of trait specific lines at ICAR-Central Horticultural Experiment Station (CIAH-RS), Panchmahals (Godhra), Gujarat during 2020–2022. In this study, we evaluated 26 gynoecious accessions to assess the genetic divergence through principal component and cluster analysis. The experiment was carried out in a randomized complete block design with three replications under rainfed semi-arid conditions. High values of PCV and GCV were observed for variables such as NFFP (25.13 and 22.20), PL (23.14 and 20.69), FD (24.01 and 21.46), AFW (22.98 and 20.13), NFPY (26.38 and 24.40), FYP (37.57 and 31.29), FY (35.55 and 33.20), AsC (28.65 and 27.73), Ac (24.32 and 21.06), TSS (37.23 and 35.94), DPPHL (20.71 and 20.38), FRAPL (21.08 and 20.92), TPF(20.81 and 20.45) respectively. High heritability coupled with high genetic advance as per cent of mean was observed for vine length (VL), internodal length (IL), number of female flowers per plant (NFFP), fruit length (FL), peduncle length (PL), fruit diameter (FD), average fruit weight (AFW), number of fruit per plant per year (NFPY), fruit yield per plant (FYP), fruit yield (FY), ascorbic acid (AsC), acidity (Ac), total soluble solids (TSS), total phenols in leaves TPL), total flavonoids in leaves TFL, CUPRAC in leaves (CUPRACL), DPPH in leaves (DPPHL), FRAP in leaves (FRAPL), Total phenols in fruits (TPF), Total flavonoids in fruits (TFF), CUPRAC in fruits (CUPRACF) and DPPH in fruits (DPPHF). The FYP exhibited a significant positive correlation with variables like VL (0.6833), IL (0.2991), NFFP (0.8107), FD (0.5245), AFW (0.6766), NFPY (0.7659), ASC (0.4611), TSS (0.5004) and TPF (0.4281). The estimates of genetic parameters revealed scope for further improvement of fruit yield by selection. Of the eight principal components, PC-I through PC-VIII had eigen values greater than 1 and it accounts 85.02% of the total variation for 26 gynoecious accessions of Ivy gourd. The eigen values of PC-I comprised 5.775% of total variation followed by PC-II (4.250%), PC-III (3.175%), PC-IV (2.588%), PC-V (1.828%), PC-VI (1.447%), PC-VII (1.179%) and PC-VIII (1.013%).The cluster VI and cluster I having highest mean values for most of traits under study. Thus, genotypes from the distinct cluster like cluster VI and I for should be used for selection of parents and varietal improvement for further breeding programme in ivy gourd.

Nutritional, antioxidants and protein profiling of leaves of Moringa oleifera germplasm

This study aimed to select elite germplasm based on nutritional, antioxidants and protein profiling of leaves of Moringa oleifera germplasm. Principal components analysis (PCA) using the fifteen nutritional traits of thirty-four accessions of M. oleifera indicated that 74.70 % variability was accounted for the first six principal components (PCs) with eigenvalues ≥1. The first principal component (PC1) had an eigenvalue of 3.6 and explained 23.90 % of the total variation. Nitrogen, protein, magnesium, iron, zinc, calcium and potassium had high positive eigenvectors in PC1. The second component (PC2) explained 15.27 % of the total variance with an eigen value of 2.29 and positively correlated to copper, calcium, phosphorus and total phenols. Protein content was significantly and highly correlated with nitrogen content in leaves (r = +1.0). High magnitude and significant correlation were found between FRAP and DPPH (r = +0.9). The thirty-four germplasm were investigated in this study on quality parameters at ICAR-Central Horticultural Experiment Station, Godhra, Gujarat, India and grouped in five main clusters. Distance estimates based on the fifteen qualitative traits ranged from 2734.15 to 3868.43. The cluster V had maximum mean values for nutrients (mg/100 g dw) iron (81.76),zinc (7.66), manganese (27.13), calcium (4470.58), magnesium (1068.28), sulfur (3758.68), nitrogen (4615.84), potassium (1558.51), protein (29.40 g/100 g), total phenols (900.21 mg GAE/100 g fw), DPPH (31.17 µmol (TE)/g fw) and FRAP (50.42 µmol (TE)/g fw). The germplasm CHES D_40 and CHES D_45 (cluster V) could be utilized for further exploration based on their nutritional, antioxidants and protein content and for conservation of nutritionally superior germplasm.

Analysis of Vision based Techniques for the Translation of Indian Sign Language

Sign language acts as a medium of communication among those of the hearing impaired and mute community. However, it cannot be easily understood by common people. Various research has been done to bridge this gap by developing Sign Language Recognition (SLR) methodologies. Studies say that 1 in every 5 deaf people is Indian.
 In this paper, a thorough review of these methodologies has been done, to compare and contrast various aspects of them. This includes an overview on different preprocessing methods used like segmentation, image morphological processing, cropping, etc, feature extraction techniques like Fourier Descriptors, Image Moments, Eigen values, Mediapipe and others. This study also covered classification models spanning from Distance metrics to Kernel based approaches and feedforward neural networks, along with Deep Learning based methods such as CNNs, LSTMs, GANs, Transformers etc.

Eigen-Chain : A unique retinopathy detecting medical image retrieval blockchain

Securing medical images is an essential requirement in healthcare industry. Managing medical image for storing patient sensitive information has remained a challenging task for researchers across the globe. Different technologies are struggling to provide a solution to the problem. Blockchain can possibly solve the security aspect problem of medical images. However, images sizes possess a difficulty in safely storing them on blockchain due to associated costs. It also creates scalability problem in blockchain. The proposed Eigen-Chain is a novel framework for creating a secure Hard Exudates detecting mechanism and storing images on blockchain using Principal Component Analysis (PCA) eigen vectors. These eigen vector can significantly reduce the images size which reduces the energy required for storage making it a sustainable model. Eigen-chain can retrieve image from blockchain efficiently. The experimental result on benchmark databases proved the superiority of proposed approach. Moreover, the Eigen-chain has been made capable of detecting exudates in the stored images making it useful in medical sector.

Agro-morphological characterization of Pakistani maize accessions using qualitative and quantitative traits.

Agro-morphological characterizations offer robust and vigorous means for the precise characterization of germplasm to be used in breeding programs. Here, agro-morphological features-based analyses were considered to figure out the genetic variability within 99 maize accessions and five (5) check varieties including Azam, W. Islamabad, Haq Nawaz, Ev-5 and Evr197. A total of 28 important agro-morphological traits were accounted in the field trails at Hazara University Mansehra Pakistan, during spring 2015. The maximum variation was detected in grain weight per cob (53.43), followed by number of kernels per row (38.64) and flag leaf area (cm2), (38.09%). Cluster analysis divided the 99 maize accession with five check varieties of maize accessions into 7 clusters following the hierarchical clustering. Cluster II recorded 29 genotypes with maximum grain yield per cob, and highest flag leaf length, followed by cluster IV. Lowest grain yield per cob was noted for accessions of cluster I. Similarly, cluster VII consisted of accession with the longest cob length. Moreover, the investigations also revealed that the primary constituent among first five principal components with an eigen value about more than 0.98 in relation to 68.75% of the total variants. PCI accounted for 25.53%, PCII contributed 18.31%, and PCIII is 9.88% of the overall morphological variability were significant contributors were grain weight per cob, number of kernel per row, 1000 grain weight. The identification of a significant level of genetic diversity during the present investigation having implications for maize germplasm characterisation, conservation, and breeding programs aiming at developing improvement maize cultivars.

Patient's satisfaction level with community pharmacies services in Romania: a questionnaire-based study.

The patient satisfaction questionnaires in literature are according to the community pharmacies services in the authors' countries and not all have psychometric reports to support the results. We designed a questionnaire specific to the services of community pharmacies in Romania to evaluate the level of patient satisfaction. We carried out a cross-sectional study on voluntary patients. The questionnaire consisted of 22 items, grouped into three domains corresponding to patient satisfaction with pharmacies, pharmaceutical staff and medication availability, and four subdomains related to pharmaceutical staff skills. The 5-point Likert scale was used. Statistical analysis was done in SPSS 27.0. The Cronbach's Alpha was 0.861. The Inter-rater Agreement was 72.0%, the Item Content Validity was 97.6% and the completeness index was 100%. The factor analysis indicated 6 factors (Eigen values >1.0). The 809 patients had a median of overall satisfaction score of 3.77; the median was 4.0 regarding satisfaction score with pharmaceutical staff skills. Respondents characteristics varied the patient's satisfaction level (p ≤ 0.05). The reliability and validity of the questionnaire have been demonstrated. Overall patient satisfaction with community pharmacy services had a moderate level, but the attitude and confidence in the pharmacist had a high level of satisfaction.

Facial Recognition Attendance Monitoring System using Deep Learning Techniques

The Facial Recognition Attendance Monitoring System employing Deep Learning Techniques represents a cutting-edge application of artificial intelligence in educational and corporate environments. The implementation of a Facial Recognition System can aid in identifying or verifying a person's identity from a digital image. Accurate attendance records are vital to classroom evaluation. However, manual attendance tracking can result in errors, missed students, or duplicate entries. The adoption of the Face Recognition-based attendance system could help eliminate these shortcomings. This innovative approach involves utilizing a camera to capture input images, detecting faces using algorithms such as Haarcascade, Eigen values, support vector machines, or the Fisher face algorithm, verifying the faces against a database of student profiles, and marking attendance in an Excel sheet. The use of OpenCV, an open-source computer vision library, ensures the efficient functioning of the system.

Development and Validation of the Companion's Satisfaction Questionnaire of Patient's Hospitalized in Intensive Care Units.

The current study aimed to develop and validate of companions' satisfaction questionnaire of patients hospitalized in ICUs. This is a methodological study that was performed in three phases: In the first phase, the concept of companion's satisfaction of patients hospitalized in ICUs was defined through qualitative content analysis method. In the second phase, early items of questionnaire were generated based on findings of the first phase. In the third and final phase, validation of the questionnaire was evaluated using face, content and construct validity as well as reliability. In exploratory factor analysis, three subscales including: satisfaction with nursing staff communication (5 items), satisfaction with nursing care (12 items), and satisfaction with decision making (5 items) were extracted by Eigen value above one and factor load above 0.5. Internal consistency and stability of the developed questionnaire confirmed with 0.94 and 0.95 respectively that indicated acceptable reliability. The 22-item developed questionnaire is valid and reliable for measurement of levels of companion's satisfaction of Iranian patients hospitalized in ICUs.

Empowering Women Agripreneurs through Government Livelihood Initiatives: A Case Study of Jharkhand, India

The study evaluates the impacts of targeted interventions implemented by the Central and state government in Jharkhand, India. Being a part of Ph.D. thesis, 260 beneficiaries from 13 blocks in three districts of Jharkhand were selected, and data was conducted during the year 2023-24. Conclusions were derived using descriptive and inferential statistics. The research revealed that all respondents were beneficiaries of the National Rural Livelihood Mission (NRLM), followed by Jharkhand Opportunities for Harnessing Rural Growth (JOHAR) (92.7%) and Jharkhand Horticulture Intensification by Micro Drip Irrigation (JHIMDI) (14.2%). The investigation also identified a substantial increase in the ownership of assets such as poly houses, poultry sheds, and micro drip systems. Income, expenditure, and savings in these areas demonstrated statistical significance after association with the programs. Income in agriculture, livestock, fisheries, and agribusiness improved significantly after receiving benefits. Principal component analysis identified three principal components with Eigen values > 1.0, with a cumulative variance of 71.03. Four entrepreneurial behavior traits-Innovativeness, Risk-bearing ability, Self-confidence, and Planning Orientation-were highly influenced by Principal Component 1, explaining 29.6 per cent of the total variance.

Eigenvector dreaming

Among the performance-enhancing procedures for Hopfield-type networks that implement associative memory, Hebbian unlearning (HU) (or dreaming) strikes for its simplicity and lucid biological interpretation. However, it does not easily lend to a clear analytical understanding. Here, we show how HU can be efficiently described in terms of the evolution of the spectrum and the eigenvectors (EVs) of the coupling matrix. That is, we find that HU barely changes the EVs of the coupling matrix, whereas the benefits of the procedure can be ascribed to an intuitive evolution of the spectrum. We use these ideas to design novel dreaming algorithms that are effective from a computational point of view and are analytically far more transparent than the original scheme.

On the principal eigenvectors of general hypergraphs

On the principal eigenvectors of general hypergraphs

Crafting a Digital Divide Index for Assessing Agricultural Disparities Among Farmers: An Application of AHP Process

a new measurement tool for assessing the digital divide disparity among farmers in e agriculture was devised during 2023-24. The index comprises four dimensions, namely ICT ownership, awareness, accessibility, and usage, respectively. For dimension selection, the researchers employed the Analytic Hierarchy Process (AHP). The maximum eigen value (ë max) of the pairwise comparison matrix was 4.0049, serving as the overall weight for the decision-making process. In the item selection process, Likert-type scale procedures were used to assess statements for final indicator selection. An interview schedule with 45 indicators was administered to 60 farmers in a non-sampling area, with five ambiguous indicators subsequently removed. The digital divide index customized for farmers demonstrated strong reliability, with a split-half reliability coefficient of 0.846 (Spearman-Brown formula) and a Pearson correlation coefficient of 0.733. Internal consistency was good, as indicated by a Cronbach’s Alpha of 0.813, and the test displayed strong validity with a score of 0.919. Overall, these findings confirm the reliability and validity of the test in measuring the intended construct. Ultimately, the 38 items were consolidated into a standardized farmers’ digital divide index for assessing agricultural disparities in the farming community.

EIGENVALUE PROBLEM AND POSITIVE SOLUTIONS FOR COUPLED SYSTEMS

We study the existence of eigen values yielding positive solutions to coupled systems. These results are obtained by using fixed point theorems in cones.

Development and Validation of Female Psychosexual Problems Scale (FPPS)

The goal of the current study was to address married women's psychosexual difficulties in the context of Pakistani culture. Semi structured interviews were conducted on 35 married females as part of the study's initial phase in order to explore phenomenology, and 34 items were created as a result. Furthermore, 34 items were initially provided to experts for the evaluation of content validity. Repetitive statements were discarded after evaluation, and a scale of 32 items was kept and approved by professionals related to psychology field. 160 married female participants were given the final 32 item scale for data collection. Factor analysis revealed a strong KMO value, and Bartlett's test of sphericity revealed a substantial connection between the items. Kaiser's criteria were used to conduct a one factor analysis and only factors with Eigen values of .4 or higher were kept, while factors with Eigen values lower than .4 were removed from the sample. Three key themes found were problems with relationships, personal suffering, and religious concerns by component analysis. Data from sample of 50 married females underwent Confirmatory Factor Analysis (CFA) to verify the variables identified through Exploratory Factor Analysis (EFA), which overall demonstrated a strong construct validity of the scale and model fit. The constructed scale's Cronbach alpha value of .97 indicates a significant inter-item correlation. The research demonstrates information on a wide range of interventions.