Innovative Practices In Teacher Education

Teacher education system is an important vehicle to improve the quality of school education. The revitalization and strengthening of the teacher education system is a powerful means for the upliftment of educational standards in the country. There are many issues that need urgent attention for improving the quality of teacher education programme. One of them is the need of innovations in teacher education programme. Innovativeness means the ability to think beyond the boundaries and create something which is different from that which already exists. Without innovations, no progress is possible. Teachers have to be innovative and their grooming has to start from their training institutions. Innovations in teacher education include IT literacy, interactive teleconferencing etc. NPE (1986) stated “The existing system of teacher education needs to be overhauled or revamped.” Unfortunately, the secondary teacher education institutions in India are stated to be largely not innovative. There are some resisting factors in our education system which prevents the teacher education institution from being innovative such as lack of physical facilities and funds, lack of diffusion of innovations among teacher educators, rigid framework, lack of research orientation etc. In this paper the authors have tried to throw light on the need of innovations required in teacher education, the resisting factors and have also given suggestions to overcome those factors. Keywords: Teacher Education, Innovation, resisting factor

Can overturning motions in penumbral filaments be detected?

Numerical simulations indicate that the filamentation of sunspot penumbrae and the associated systematic outflow (the Evershed effect) are due to convectively driven fluid motions constrained by the inclined magnetic field. We investigate whether these motions, in particular the upflows in the bright filaments and the downflows at their edges can be reliably observed with existing instrumentation. We use a snapshot from a sunspot simulation to calculate 2D maps of synthetic line profiles for the spectral lines Fe\sci 7090.4 \AA ~ and C\sci 5380.34 \AA. The maps are spatially and spectrally degraded according to typical instrument properties. Line-of-sight velocities are determined from line bisector shifts. We find that the detectability of the convective flows is strongly affected by spatial smearing, particularly so for the downflows. Furthermore, the line-of-sight velocities are dominated by the Evershed flow unless the observation is made very near to disk center. These problems may have compromised recent attempts to detect overturning penumbral convection. Lines with a low formation height are best suited to detect the convective flows.Comment: 8 pages, 12 figures, accepted for publication in ApJ on 28th Ju

DQLRFMG: Design of an Augmented Fusion of Deep Q Learning with Logistic Regression and Deep Forests for Multivariate Classification and Grading of Fruits

Accurate categorization and grading of fruits are essential in numerous fields, including agriculture, food processing, and distribution. This paper addresses the need for an advanced model capable of classifying and grading fruits more effectively than existing methods. Traditional approaches are limited by their lower precision, accuracy, recall, area under the curve (AUC), and delay. In order to overcome these obstacles, the proposed model combines the capabilities of Deep Q Learning (DQL) for classification and Logistic Regression (LR) with Deep Forests for fruit grading process. Three distinct datasets were used to evaluate the model: the Kaggle - Fruits 360 Dataset, the FRont Experimental System for High throughput plant phenotyping Datasets, and ImageNet samples. In multiple respects, comparative analysis demonstrates that the proposed model outperforms existing methods. Specifically, it achieves a remarkable 4.9% improvement in precision, 5.5% improvement in accuracy, 4.5% improvement in recall, 3.9% improvement in AUC, and an 8.5% reduction in delay levels. Utilizing the strengths of both DQL and LR with Deep Forests, the proposed model achieves its superior performance. DQL, a technique for reinforcement learning, provides the ability to learn and make decisions based on the feedback from the environment. By combining DQL and LR, the classification accuracy is improved, allowing for the precise identification of fruit varieties including Mango, Apple. Papaya, etc. In addition, Deep Forests, a novel framework for ensemble learning, is utilized for fruit grading. Deep Forests utilizes decision trees to effectively capture complex patterns in the data, allowing for dependable and robust fruit grading. Experimental findings indicate that the combination of DQL and LR with Deep Forests yields remarkable performance improvements in fruit classification and grading tasks. Improved precision, accuracy, recall, AUC, and delay indicate the model's superiority over existing methods. This research contributes to the field of fruit classification and grading by developing a sophisticated model that can support a variety of applications in the agriculture, food processing, and distribution industries

Meaningful Clinical Conversation: Guidance from the Gita

Chronic disease care is a challenging vocation. One of the reasons for this is the need to inform and share decision making with patients. Communication and conversational skills are the pillars of chronic care delivery. In this editorial, we take guidance from the Srimad Bhagavad Gita in order to improve the quality of clinical conversations, and make them meaningful. The Gita encourages us to be ‘saatvik’ or balanced in thought, words and deeds, to perform ‘penance’ of mind, speech and body, and to accept equanimity. This introspective opinion piece should help us polish our communication skills, and improve interaction with our patients

The Spirit and Science: Is the Endocrine System the Essence of Existence?

In this reflective opinion piece, the authors offer a unique insight into the connection between spirituality and science. A reading of the Shrimad Bhagvad Gita, through the eyes of an endocrinologist, uncovers unexpected corollaries and correlations between spirituality or religion on one hand, and science or rationale, on the other

Generalized fixed point theorems on metric spaces

In this paper, we establish some fixed point theorems for single valued and multi-valued mappings on a complete metric space. Suzuki's and some other fixed point theorems are generalized by taking a more general contractive condition for single valued mappings. It is also proved that our result characterizes the completeness of the metric space. Further, taking generalized contractive condition, a fixed point theorem is also established for multi-valued mappings

Chromospheric plasma ejection above a pore

We present high spatial resolution observations of short lived transients, ribbon and jets like events above a pore in Ca II H images where fine structure like umbral dots, lightbridge and penumbral micro filaments are present in the underlying photosphere. We found that current layers are formed at the edges of convective fine structure due to the shear between their horizontal field and the ambient vertical field. High vertical electric current density patches are observed in the photosphere around these events which indicates the formation of a current sheet at the reconnection site. In the framework of past studies, low altitude reconnection could be the mechanism that produces such events. The reconnection is caused by an opposite polarity field produced by the bending of field lines by convective downflows at the edge of the pore fine structures.Comment: 10 pages, 5 figures, accepted for publication in MNRA

Influencing Factors of Behavior Intention and Actual Use of Technology: An Application of UTAUT Model on Science Undergraduates

This study was conducted by empirically testing a model to predict the factors affecting science undergraduates’ behaviour intentions towards the actual use of technology (digital leaning). This study explored the behavioural intention of use of digital learning from the perspective of students by applying the extended UTAUT model. A cross-sectional study was conducted on science undergraduates. The data was derived from an online survey with 425 respondents and analyzed using a structural equation model. PLS-SEM was used for model and hypothesis testing. The result revealed that performance expectancy, effort expectancy, and social influence are positively associated with behaviour intention and actual use of technology. Facilitating conditions were negatively associated with BIUT (behavior intention and actual use of technology). Our findings correspond with the UTAUT model and provide a practical reference for educational institutions on designing digital learning for further studies

Genetic analysis of SLC47A1, SLC22A1, SLC22A2, ATM gene polymorphisms among diabetics in an Indian population

Background: Metformin is a first-line therapy for type 2 diabetes mellitus. However, the glycaemic response to metformin is likely to be affected by polymorphisms of transporter genes. Therefore, the study was done with the  aim to assess demographic distribution of transporter genotypes involved in disposition and action of metformin.Methods: This cross-sectional, observational, single centre, clinical study was conducted in 80 diabetic patients recruited from medicine OPD. Descriptive analysis was done for distribution of the four transporter genotypes viz. SLC47A1 (rs2289669), ATM (rs11212617), SLC22A2 (rs316019) and SLC22A1 (rs622342). Genotyping was determined by DNA extraction, agarose gel electrophoresis, estimation of DNA concentration, polymerase chain reaction, DNA sequencing, sequencing analysis.Results: Transporter genotype analysis showed that for SLC47A1 (rs2289669) transporter, 31.25% and 26.25% were homozygous for AA and GG allele respectively, while 42.5% were heterozygous (AG). For ATM (rs11212617), SLC22A2 (rs316019) and SLC22A1 (rs622342) transporter, 45% and 10%, 1.25% and 80%, 58.75% and 7.50% were homozygous for AA and CC allele respectively; while 45%, 18.75%, 33.75% were heterozygous (AC) respectively. Interethnic differences in the genotype and allele frequencies of SLC22A1 (rs622342) and ATM (rs11212617) gene polymorphism were observed when compared with other major populations.Conclusions: In the genotypic distribution of four transporter genotype study showed that there was an ethnic variation in allelic distribution of allele A and C of ATM (rs11212617) and SLC22A1 (rs622342) while AA genotype of SLC22A2 (rs316019) was rare genotype and allele ‘A’ was major allele found in our study. The study data observed would justify further pharmacogenetic studies to evaluate the role of gene polymorphism in the therapeutic efficacy of metformin.

Spectropolarimetery of umbral fine structures from Hinode: Evidence for magnetoconvection

We present spectropolarimetric analysis of umbral dots and a light bridge fragment that show dark lanes in G-band images. Umbral dots show upflow as well as associated positive Stokes V area asymmetry in their central parts. Larger umbral dots show down flow patches in their surrounding parts that are associated with negative Stokes V area asymmetry. Umbral dots show weaker magnetic field in central part and higher magnetic field in peripheral area. Umbral fine structures are much better visible in total circularly polarized light than in continuum intensity. Umbral dots show a temperature deficit above dark lanes. The magnetic field inclination show a cusp structure above umbral dots and a light bridge fragment. We compare our observational findings with 3D magnetohydrodynamic simulations.Comment: Accepted for publication in MNRAS, 6 pages, 6 figure